ALBERT

Beschreibung: Motivation: High-throughput sequencing (HTS) technologies have made low-cost sequencing of large numbers of samples commonplace. An explosion in the type, not just number, of sequencing experiments has also taken place including genome re-sequencing, population-scale variation detection, whole transcriptome sequencing and genome-wide analysis of protein-bound nucleic acids. Results: We present Artemis as a tool for integrated visualization and computational analysis of different types of HTS datasets in the context of a reference genome and its corresponding annotation. Availability: Artemis is freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute websites: http://www.sanger.ac.uk/resources/software/artemis/ . Contact: artemis@sanger.ac.uk ; tjc@sanger.ac.uk

Beschreibung: : microRibonucleic acid (miRNAs) are small regulatory molecules that act by mRNA degradation or via translational repression. Although many miRNAs are ubiquitously expressed, a small subset have differential expression patterns that may give rise to tissue-specific complexes. Motivation: This work studies gene targeting patterns amongst miRNAs with differential expression profiles, and links this to control and regulation of protein complexes. Results: We find that, when a pair of miRNAs are not expressed in the same tissues, there is a higher tendency for them to target the direct partners of the same hub proteins. At the same time, they also avoid targeting the same set of hub-spokes. Moreover, the complexes corresponding to these hub-spokes tend to be specific and nonoverlapping. This suggests that the effect of miRNAs on the formation of complexes is specific. Contact: wongls@comp.nus.edu.sg Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Small interfering RNAs (siRNAs) are produced from much longer sequences of double-stranded RNA precursors through cleavage by Dicer or a Dicer-like protein. These small RNAs play a key role in genetic and epigenetic regulation; however, a full understanding of the mechanisms by which they operate depends on the characterization of the precursors from which they are derived. Results: High-throughput sequencing of small RNA populations allows the locations of the double-stranded RNA precursors to be inferred. We have developed methods to analyse small RNA sequencing data from multiple biological sources, taking into account replicate information, to identify robust sets of siRNA precursors. Our methods show good performance on both a set of small RNA sequencing data in Arabidopsis thaliana and simulated datasets. Availability: Our methods are available as the Bioconductor ( www.bioconductor.org ) package segmentSeq (version 1.5.6 and above). Contact: tjh48@cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Intrinsically disordered regions are key for the function of numerous proteins, and the scant available experimental annotations suggest the existence of different disorder flavors. While efficient predictions are required to annotate entire genomes, most existing methods require sequence profiles for disorder prediction, making them cumbersome for high-throughput applications. Results: In this work, we present an ensemble of protein disorder predictors called ESpritz. These are based on bidirectional recursive neural networks and trained on three different flavors of disorder, including a novel NMR flexibility predictor. ESpritz can produce fast and accurate sequence-only predictions, annotating entire genomes in the order of hours on a single processor core. Alternatively, a slower but slightly more accurate ESpritz variant using sequence profiles can be used for applications requiring maximum performance. Two levels of prediction confidence allow either to maximize reasonable disorder detection or to limit expected false positives to 5%. ESpritz performs consistently well on the recent CASP9 data, reaching a S w measure of 54.82 and area under the receiver operator curve of 0.856. The fast predictor is four orders of magnitude faster and remains better than most publicly available CASP9 methods, making it ideal for genomic scale predictions. Conclusions: ESpritz predicts three flavors of disorder at two distinct false positive rates, either with a fast or slower and slightly more accurate approach. Given its state-of-the-art performance, it can be especially useful for high-throughput applications. Availability: Both a web server for high-throughput analysis and a Linux executable version of ESpritz are available from: http://protein.bio.unipd.it/espritz/ Contact: silvio.tosatto@unipd.it Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Clustering protein structures is an important task in structural bioinformatics. De novo structure prediction, for example, often involves a clustering step for finding the best prediction. Other applications include assigning proteins to fold families and analyzing molecular dynamics trajectories. Results: We present Pleiades, a novel approach to clustering protein structures with a rigorous mathematical underpinning. The method approximates clustering based on the root mean square deviation by first mapping structures to Gauss integral vectors—which were introduced by Røgen and co-workers—and subsequently performing K-means clustering. Conclusions: Compared to current methods, Pleiades dramatically improves on the time needed to perform clustering, and can cluster a significantly larger number of structures, while providing state-of-the-art results. The number of low energy structures generated in a typical folding study, which is in the order of 50 000 structures, can be clustered within seconds to minutes. Contact: thamelry@binf.ku.dk ; harder@binf.ku.dk Supplementary Information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Transmembrane β barrel proteins (TMBs) are found in the outer membrane of Gram-negative bacteria, chloroplast and mitochondria. They play a major role in the translocation machinery, pore formation, membrane anchoring and ion exchange. TMBs are also promising targets for antimicrobial drugs and vaccines. Given the difficulty in membrane protein structure determination, computational methods to identify TMBs and predict the topology of TMBs are important. Results: Here, we present BOCTOPUS; an improved method for the topology prediction of TMBs by employing a combination of support vector machines (SVMs) and Hidden Markov Models (HMMs). The SVMs and HMMs account for local and global residue preferences, respectively. Based on a 10-fold cross-validation test, BOCTOPUS performs better than all existing methods, reaching a Q3 accuracy of 87%. Further, BOCTOPUS predicted the correct number of strands for 83% proteins in the dataset. BOCTOPUS might also help in reliable identification of TMBs by using it as an additional filter to methods specialized in this task. Availability: BOCTOPUS is freely available as a web server at: http://boctopus.cbr.su.se/ . The datasets used for training and evaluations are also available from this site. Contact: arne@bioinfo.se Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: High-dimensional data such as microarrays have created new challenges to traditional statistical methods. One such example is on class prediction with high-dimension, low-sample size data. Due to the small sample size, the sample mean estimates are usually unreliable. As a consequence, the performance of the class prediction methods using the sample mean may also be unsatisfactory. To obtain more accurate estimation of parameters some statistical methods, such as regularizations through shrinkage, are often desired. Results: In this article, we investigate the family of shrinkage estimators for the mean value under the quadratic loss function. The optimal shrinkage parameter is proposed under the scenario when the sample size is fixed and the dimension is large. We then construct a shrinkage-based diagonal discriminant rule by replacing the sample mean by the proposed shrinkage mean. Finally, we demonstrate via simulation studies and real data analysis that the proposed shrinkage-based rule outperforms its original competitor in a wide range of settings. Contact: tongt@hkbu.edu.hk

Beschreibung: Motivation: The advent of high-throughput sequencing technologies is revolutionizing our ability in discovering and genotyping DNA copy number variants (CNVs). Read count-based approaches are able to detect CNV regions with an unprecedented resolution. Although this computational strategy has been recently introduced in literature, much work has been already done for the preparation, normalization and analysis of this kind of data. Results: Here we face the many aspects that cover the detection of CNVs by using read count approach. We first study the characteristics and systematic biases of read count distributions, focusing on the normalization methods designed for removing these biases. Subsequently, we compare the algorithms designed to detect the boundaries of CNVs and we investigate the ability of read count data to predict the exact number of DNA copy. Finally, we review the tools publicly available for analysing read count data. To better understand the state of the art of read count approaches, we compare the performance of the three most widely used sequencing technologies (Illumina Genome Analyzer, Roche 454 and Life Technologies SOLiD) in all the analyses that we perform. Contact: albertomagi@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: We investigate and quantify the generalizability of the white blood cell (WBC) transcriptome to the general, multiorgan transcriptome. We use data from the NCBI's Gene Expression Omnibus (GEO) public repository to define two datasets for comparison, WBC and OO (Other Organ) sets. Results: Comprehensive pair-wise correlation and expression level profiles are calculated for both datasets (with sizes of 81 and 1463, respectively). We have used mapping and ranking across the Gene Ontology (GO) categories to quantify similarity between the two sets. GO mappings of the most correlated and highly expressed genes from the two datasets tightly match, with the notable exceptions of components of the ribosome, cell adhesion and immune response. That is, 10 877 or 48.8% of all measured genes do not change 〉10% of rank range between WBC and OO; only 878 (3.9%) change rank 〉50%. Two trans -tissue gene lists are defined, the most changing and the least changing genes in expression rank. We also provide a general, quantitative measure of the probability of expression rank and correlation profile in the OO system given the expression rank and correlation profile in the WBC dataset. Contact: vvaltchinov@partners.org Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: The understanding of the molecular sources for diseases like cancer can be significantly improved by computational models. Recently, Boolean networks have become very popular for modeling signaling and regulatory networks. However, such models rely on a set of Boolean functions that are in general not known. Unfortunately, while detailed information on the molecular interactions becomes available in large scale through electronic databases, the information on the Boolean functions does not become available simultaneously and has to be included manually into the models, if at all known. Results: We propose a new Boolean approach which can directly utilize the mechanistic network information available through modern databases. The Boolean function is implicitly defined by the reaction mechanisms. Special care has been taken for the treatment of kinetic features like inhibition. The method has been applied to a signaling model combining the Wnt and MAPK pathway. Availability: A sample C++ implementation of the proposed method is available for Linux and compatible systems through http://code.google.com/p/libscopes/wiki/Paper2011 Contact: handorf@physik.hu-berlin.de Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Multiple sequence alignment (MSA) is a core method in bioinformatics. The accuracy of such alignments may influence the success of downstream analyses such as phylogenetic inference, protein structure prediction, and functional prediction. The importance of MSA has lead to the proliferation of MSA methods, with different objective functions and heuristics to search for the optimal MSA. Different methods of inferring MSAs produce different results in all but the most trivial cases. By measuring the differences between inferred alignments, we may be able to develop an understanding of how these differences (i) relate to the objective functions and heuristics used in MSA methods, and (ii) affect downstream analyses. Results: We introduce four metrics to compare MSAs, which include the position in a sequence where a gap occurs or the location on a phylogenetic tree where an insertion or deletion (indel) event occurs. We use both real and synthetic data to explore the information given by these metrics and demonstrate how the different metrics in combination can yield more information about MSA methods and the differences between them. Availability: MetAl is a free software implementation of these metrics in Haskell. Source and binaries for Windows, Linux and Mac OS X are available from http://kumiho.smith.man.ac.uk/whelan/software/metal/ . Contact: simon.whelan@manchester.ac.uk

Beschreibung: Motivation: Peptide detection is a crucial step in mass spectrometry (MS) based proteomics. Most existing algorithms are based upon greedy isotope template matching and thus may be prone to error propagation and ineffective to detect overlapping peptides. In addition, existing algorithms usually work at different charge states separately, isolating useful information that can be drawn from other charge states, which may lead to poor detection of low abundance peptides. Results: BPDA2d models spectra as a mixture of candidate peptide signals and systematically evaluates all possible combinations of possible peptide candidates to interpret the given spectra. For each candidate, BPDA2d takes into account its elution profile, charge state distribution and isotope pattern, and it combines all evidence to infer the candidate's signal and existence probability. By piecing all evidence together—especially by deriving information across charge states—low abundance peptides can be better identified and peptide detection rates can be improved. Instead of local template matching, BPDA2d performs global optimization for all candidates and systematically optimizes their signals. Since BPDA2d looks for the optimal among all possible interpretations of the given spectra, it has the capability in handling complex spectra where features overlap. BPDA2d estimates the posterior existence probability of detected peptides, which can be directly used for probability-based evaluation in subsequent processing steps. Our experiments indicate that BPDA2d outperforms state-of-the-art detection methods on both simulated data and real liquid chromatography–mass spectrometry data, according to sensitivity and detection accuracy. Availability: The BPDA2d software package is available at http://gsp.tamu.edu/Publications/supplementary/sun11a/ Contact: Michelle.Zhang@utsa.edu ; edward@ece.tamu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: The continued progress in developing technological platforms, availability of many published experimental datasets, as well as different statistical methods to analyze those data have allowed approaching the same research question using various methods simultaneously. To get the best out of all these alternatives, we need to integrate their results in an unbiased manner. Prioritized gene lists are a common result presentation method in genomic data analysis applications. Thus, the rank aggregation methods can become a useful and general solution for the integration task. Results: Standard rank aggregation methods are often ill-suited for biological settings where the gene lists are inherently noisy. As a remedy, we propose a novel robust rank aggregation (RRA) method. Our method detects genes that are ranked consistently better than expected under null hypothesis of uncorrelated inputs and assigns a significance score for each gene. The underlying probabilistic model makes the algorithm parameter free and robust to outliers, noise and errors. Significance scores also provide a rigorous way to keep only the statistically relevant genes in the final list. These properties make our approach robust and compelling for many settings. Availability: All the methods are implemented as a GNU R package R obust R ank A ggreg , freely available at the Comprehensive R Archive Network http://cran.r-project.org/ . Contact: vilo@ut.ee Supplementary information Supplementary data are available at Bioinformatics online.

Beschreibung: : CLARE is a computational method designed to reveal sequence encryption of tissue-specific regulatory elements. Starting with a set of regulatory elements known to be active in a particular tissue/process, it learns the sequence code of the input set and builds a predictive model from features specific to those elements. The resulting model can then be applied to user-supplied genomic regions to identify novel candidate regulatory elements. CLARE's model also provides a detailed analysis of transcription factors that most likely bind to the elements, making it an invaluable tool for understanding mechanisms of tissue-specific gene regulation. Availability: CLARE is freely accessible at http://clare.dcode.org/ . Contact: taherl@ncbi.nlm.nih.gov ; ovcharen@nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: We present a pipeline for the pre-processing, quality assessment, read distribution and methylation estimation for methylated DNA immunoprecipitation (MeDIP)-sequence datasets. This is the first MeDIP-seq-specific analytic pipeline that starts at the output of the sequencers. This pipeline will reduce the data analysis load on staff and allows the easy and straightforward analysis of sequencing data for DNA methylation. The pipeline integrates customized scripting and several existing tools, which can deal with both paired and single end data. Availability: The package and extensive documentation, and comparison to public data is available at http://life.tongji.edu.cn/meqa/ Contact: jhuang@cephb.fr

Beschreibung: Motivation: A plethora of bioinformatics analysis has led to the discovery of numerous gene sets, which can be interpreted as discrete measurements emitted from latent signaling pathways. Their potential to infer signaling pathway structures, however, has not been sufficiently exploited. Existing methods accommodating discrete data do not explicitly consider signal cascading mechanisms that characterize a signaling pathway. Novel computational methods are thus needed to fully utilize gene sets and broaden the scope from focusing only on pairwise interactions to the more general cascading events in the inference of signaling pathway structures. Results: We propose a gene set based simulated annealing (SA) algorithm for the reconstruction of signaling pathway structures. A signaling pathway structure is a directed graph containing up to a few hundred nodes and many overlapping signal cascades, where each cascade represents a chain of molecular interactions from the cell surface to the nucleus. Gene sets in our context refer to discrete sets of genes participating in signal cascades, the basic building blocks of a signaling pathway, with no prior information about gene orderings in the cascades. From a compendium of gene sets related to a pathway, SA aims to search for signal cascades that characterize the optimal signaling pathway structure. In the search process, the extent of overlap among signal cascades is used to measure the optimality of a structure. Throughout, we treat gene sets as random samples from a first-order Markov chain model. We evaluated the performance of SA in three case studies. In the first study conducted on 83 KEGG pathways, SA demonstrated a significantly better performance than Bayesian network methods. Since both SA and Bayesian network methods accommodate discrete data, use a ‘search and score’ network learning strategy and output a directed network, they can be compared in terms of performance and computational time. In the second study, we compared SA and Bayesian network methods using four benchmark datasets from DREAM. In our final study, we showcased two context-specific signaling pathways activated in breast cancer. Availibility: Source codes are available from http://dl.dropbox.com/u/16000775/sa_sc.zip Contact: dzhu@wayne.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : We provide a Bioconductor package with quality assessment, processing and visualization tools for high-throughput sequencing data, with emphasis in ChIP-seq and RNA-seq studies. It includes detection of outliers and biases, inefficient immuno-precipitation and overamplification artifacts, de novo identification of read-rich genomic regions and visualization of the location and coverage of genomic region lists. Availability: www.bioconductor.org Contact: david.rossell@irbbarcelona.org Supplementary information: Supplementary data available at Bioinformatics online.

Beschreibung: Motivation: We study a stochastic method for approximating the set of local minima in partial RNA folding landscapes associated with a bounded-distance neighbourhood of folding conformations. The conformations are limited to RNA secondary structures without pseudoknots. The method aims at exploring partial energy landscapes p L induced by folding simulations and their underlying neighbourhood relations. It combines an approximation of the number of local optima devised by Garnier and Kallel (2002) with a run-time estimation for identifying sets of local optima established by Reeves and Eremeev (2004). Results: The method is tested on nine sequences of length between 50 nt and 400 nt, which allows us to compare the results with data generated by RNAsubopt and subsequent barrier tree calculations. On the nine sequences, the method captures on average 92% of local minima with settings designed for a target of 95%. The run-time of the heuristic can be estimated by O ( n 2 D ln), where n is the sequence length, is the number of local minima in the partial landscape p L under consideration and D is the maximum number of steepest descent steps in attraction basins associated with p L . Contact: a.albrecht@qub.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: RNA-seq is a powerful technology for the study of transcriptome profiles that uses deep-sequencing technologies. Moreover, it may be used for cellular phenotyping and help establishing the etiology of diseases characterized by abnormal splicing patterns. In RNA-Seq, the exact nature of splicing events is buried in the reads that span exon–exon boundaries. The accurate and efficient mapping of these reads to the reference genome is a major challenge. Results: We developed PASSion, a pattern growth algorithm-based pipeline for splice site detection in paired-end RNA-Seq reads. Comparing the performance of PASSion to three existing RNA-Seq analysis pipelines, TopHat, MapSplice and HMMSplicer, revealed that PASSion is competitive with these packages. Moreover, the performance of PASSion is not affected by read length and coverage. It performs better than the other three approaches when detecting junctions in highly abundant transcripts. PASSion has the ability to detect junctions that do not have known splicing motifs, which cannot be found by the other tools. Of the two public RNA-Seq datasets, PASSion predicted ~ 137 000 and 173 000 splicing events, of which on average 82 are known junctions annotated in the Ensembl transcript database and 18% are novel. In addition, our package can discover differential and shared splicing patterns among multiple samples. Availability: The code and utilities can be freely downloaded from https://trac.nbic.nl/passion and ftp://ftp.sanger.ac.uk/pub/zn1/passion Contact: y.zhang@lumc.nl ; k.ye@lumc.nl Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: The completion of 168 genome sequences from a single population of Drosophila melanogaster provides a global view of genomic variation and an understanding of the evolutionary forces shaping the patterns of DNA polymorphism and divergence along the genome. Results: We present the ‘Population Drosophila Browser’ (PopDrowser), a new genome browser specially designed for the automatic analysis and representation of genetic variation across the D. melanogaster genome sequence. PopDrowser allows estimating and visualizing the values of a number of DNA polymorphism and divergence summary statistics, linkage disequilibrium parameters and several neutrality tests. PopDrowser also allows performing custom analyses on-the-fly using user-selected parameters. Availability: PopDrowser is freely available from http://PopDrowser.uab.cat . Contact: miquel.ramia@uab.cat

Beschreibung: Motivation: Probabilistic approaches for inferring transcription factor binding sites (TFBSs) and regulatory motifs from DNA sequences have been developed for over two decades. Previous work has shown that prediction accuracy can be significantly improved by incorporating features such as the competition of multiple transcription factors (TFs) for binding to nearby sites, the tendency of TFBSs for co-regulated TFs to cluster and form cis -regulatory modules and explicit evolutionary modeling of conservation of TFBSs across orthologous sequences. However, currently available tools only incorporate some of these features, and significant methodological hurdles hampered their synthesis into a single consistent probabilistic framework. Results: We present MotEvo, a integrated suite of Bayesian probabilistic methods for the prediction of TFBSs and inference of regulatory motifs from multiple alignments of phylogenetically related DNA sequences, which incorporates all features just mentioned. In addition, MotEvo incorporates a novel model for detecting unknown functional elements that are under evolutionary constraint, and a new robust model for treating gain and loss of TFBSs along a phylogeny. Rigorous benchmarking tests on ChIP-seq datasets show that MotEvo's novel features significantly improve the accuracy of TFBS prediction, motif inference and enhancer prediction. Availability: Source code, a user manual and files with several example applications are available at www.swissregulon.unibas.ch . Contact: erik.vannimwegen@unibas.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : We present LaTcOm, a new web tool, which offers several alternative methods for ‘rare codon cluster’ (RCC) identification from a single and simple graphical user interface. In the current version, three RCC detection schemes are implemented: the recently described %MinMax algorithm and a simplified sliding window approach, along with a novel modification of a linear-time algorithm for the detection of maximally scoring subsequences tailored to the RCC detection problem. Among a number of user tunable parameters, several codon-based scales relevant for RCC detection are available, including tRNA abundance values from Escherichia coli and several codon usage tables from a selection of genomes. Furthermore, useful scale transformations may be performed upon user request (e.g. linear, sigmoid). Users may choose to visualize RCC positions within the submitted sequences either with graphical representations or in textual form for further processing. Availability: LaTcOm is freely available online at the URL http://troodos.biol.ucy.ac.cy/latcom.html . Contact: vprobon@ucy.ac.cy Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : Many existing databases annotate experimentally characterized single nucleotide polymorphisms (SNPs). Each non-synonymous SNP (nsSNP) changes one amino acid in the gene product (single amino acid substitution;SAAS). This change can either affect protein function or be neutral in that respect. Most polymorphisms lack experimental annotation of their functional impact. Here, we introduce SNPdbe—SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from 〉2600 organisms; ‘human’ being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt. SNPdbe is consistently updated and easily augmented with new sources of information. The database is available as an MySQL dump and via a web front end that allows searches with any combination of organism names, sequences and mutation IDs. Availability: http://www.rostlab.org/services/snpdbe Contact: schaefer@rostlab.org ; snpdbe@rostlab.org

Beschreibung: : We have implemented in a single package all the features required for extracting, visualizing and manipulating fully conserved positions as well as those with a family-dependent conservation pattern in multiple sequence alignments. The program allows, among other things, to run different methods for extracting these positions, combine the results and visualize them in protein 3D structures and sequence spaces. Availability and implementation: JDet is a multiplatform application written in Java. It is freely available, including the source code, at http://csbg.cnb.csic.es/JDet . The package includes two of our recently developed programs for detecting functional positions in protein alignments ( Xdet and S3Det ), and support for other methods can be added as plug-ins. A help file and a guided tutorial for JDet are also available. Contact: pazos@cnb.csic.es

Beschreibung: : VarSifter is a graphical software tool for desktop computers that allows investigators of varying computational skills to easily and quickly sort, filter, and sift through sequence variation data. A variety of filters and a custom query framework allow filtering based on any combination of sample and annotation information. By simplifying visualization and analyses of exome-scale sequence variation data, this program will help bring the power and promise of massively-parallel DNA sequencing to a broader group of researchers. Availability and Implementation: VarSifter is written in Java, and is freely available in source and binary versions, along with a User Guide, at http://research.nhgri.nih.gov/software/VarSifter/ . Contact: mullikin@mail.nih.gov Supplementary Information: Additional figures and methods available online at the journal's website.

Beschreibung: Insect cells are widely used for recombinant glycoprotein production, but they cannot provide the glycosylation patterns required for some biotechnological applications. This problem has been addressed by genetically engineering insect cells to express mammalian genes encoding various glycoprotein glycan processing functions. However, for various reasons, the impact of a mammalian cytosine-5'-monophospho (CMP)-sialic acid transporter has not yet been examined. Thus, we transformed Spodoptera frugiperda (Sf9) cells with six mammalian genes to generate a new cell line, SfSWT-4, that can produce sialylated glycoproteins when cultured with the sialic acid precursor, N -acetylmannosamine. We then super-transformed SfSWT-4 with a human CMP-sialic acid transporter (hCSAT) gene to isolate a daughter cell line, SfSWT-6, which expressed the hCSAT gene in addition to the other mammalian glycogenes. SfSWT-6 cells had higher levels of cell surface sialylation and also supported higher levels of recombinant glycoprotein sialylation, particularly when cultured with low concentrations of N -acetylmannosamine. Thus, hCSAT expression has an impact on glycoprotein sialylation, can reduce the cost of recombinant glycoprotein production and therefore should be included in ongoing efforts to glycoengineer the baculovirus-insect cell system. The results of this study also contributed new insights into the endogenous mechanism and potential mechanisms of CMP-sialic acid accumulation in the Golgi apparatus of lepidopteran insect cells.

Beschreibung: Chondroitin sulfate (CS) chains regulate the development of the central nervous system in vertebrates and are linear polysaccharides consisting of variously sulfated repeating disaccharides, [–4GlcUAβ1-3GalNAcβ1–] n , where GlcUA and GalNAc represent d -glucuronic acid and N -acetyl- d -galactosamine, respectively. CS chains containing D-disaccharide units [GlcUA(2- O -sulfate)-GalNAc(6- O -sulfate)] are involved in the development of cerebellar Purkinje cells and neurite outgrowth-promoting activity through interaction with a neurotrophic factor, pleiotrophin, resulting in the regulation of signaling. In this study, to obtain further structural information on the CS chains containing d -disaccharide units involved in brain development, oligosaccharides containing D-units were isolated from a shark fin cartilage. Seven novel hexasaccharide sequences, O-D-D, A-D-D, C-D-D, E-A-D, D-D-C, E-D-D and A-B-D, in addition to three previously reported sequences, C-A-D, C-D-C and A-D-A, were isolated from a CS preparation of shark fin cartilage after exhaustive digestion with chondroitinase AC-I, which cannot act on the galactosaminidic linkages bound to D-units. The symbol stands for a 4,5-unsaturated bond of uronic acids, whereas A, B, C, D, E and O represent [GlcUA-GalNAc(4- O -sulfate)], [GlcUA(2- O -sulfate)-GalNAc(4- O -sulfate)], [GlcUA-GalNAc(6- O -sulfate)], [GlcUA(2- O -sulfate)-GalNAc(6- O -sulfate)], [GlcUA-GalNAc(4- O -, 6- O -sulfate)] and [GlcUA-GalNAc], respectively. In binding studies using an anti-CS monoclonal antibody, MO-225, the epitopes of which are involved in cerebellar development in mammals, novel epitope structures, A-D-A, A-D-D and A-B-D, were revealed. Hexasaccharides containing two consecutive D-units or a B-unit will be useful for the structural and functional analyses of CS chains particularly in the neuroglycobiological fields.

Beschreibung: Protein O -fucosyltransferase 1 (Pofut1) and protein O -fucosyltransferase 2 (Pofut2) add O -linked fucose at distinct consensus sequences in properly folded epidermal growth factor (EGF)-like repeats and thrombospondin type-1 (TSR) repeats, respectively. Glycan chain elongation past O -fucose can occur to yield a tetrasaccharide on EGF repeats and a disaccharide on TSRs. Elimination of Pofut1 in mice causes embryonic lethality with Notch-like phenotypes demonstrating that O -fucosylation of Notch is essential for its function. Similarly, elimination of Pofut2 results in an early embryonic lethal phenotype in mice, although the molecular mechanism for the lethality is unknown. The recent development of sugar analogs has revolutionized the study of glycans by providing a convenient method for labeling and tracking glycosylation. In order to study O -fucosylation, we took advantage of the recently developed reporter, 6-alkynyl fucose. Using the Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC), or "click" reaction, azido-biotin allows tagging and detection of 6AF-modified proteins. Here we examine whether proteins containing EGF repeats or TSRs with O -fucose consensus sequences are specifically modified with 6AF in cell culture. Using mass spectrometry (MS), we demonstrate that 6AF is efficiently incorporated onto the appropriate consensus sequences on EGF repeats and TSRs. Furthermore, the elongation of the O -fucose monosaccharide on EGF repeats and TSRs is not hampered when 6AF is used. These results show that 6AF is efficiently utilized in a truly bioorthogonal manner by Pofut1, Pofut2 and the enzymes that elongate O -fucose, providing evidence that 6AF is a significant new tool in the study of protein O -fucosylation.

Beschreibung: Xanthan is a polysaccharide secreted by Xanthomonas campestris that contains pentameric repeat units. The biosynthesis of xanthan involves an operon composed of 12 genes ( gumB to gumM ). In this study, we analyzed the proteins encoded by gumB and gumC . Membrane fractionation showed that GumB was mainly associated with the outer membrane, whereas GumC was an inner membrane protein. By in silico analysis and specific globomycin inhibition, GumB was characterized as a lipoprotein. By reporter enzyme assays, GumC was shown to contain two transmembrane segments flanking a large periplasmic domain. We confirmed that gumB and gumC mutant strains uncoupled the synthesis of the lipid-linked repeat unit from the polymerization process. We studied the effects of gumB and gumC gene amplification on the production, composition and viscosity of xanthan. Overexpression of GumB, GumC or GumB and GumC simultaneously did not affect the total amount or the chemical composition of the polymer. GumB overexpression did not affect xanthan viscosity; however, a moderate increase in xanthan viscosity was achieved when GumC protein levels were increased 5-fold. Partial degradation of GumC was observed when only that protein was overexpressed; but co-expression of GumB and GumC diminished GumC degradation and resulted in higher xanthan viscosity than individual GumB or GumC overexpression. Compared with xanthan from the wild-type strain, longer polymer chains from the strain that simultaneously overexpressed GumB and GumC were observed by atomic force microscopy. Our results suggest that GumB–GumC protein levels modulate xanthan chain length, which results in altered polymer viscosity.

Beschreibung: Bifidobacterium bifidum is one of the most frequently found bifidobacteria in the intestines of newborn infants. We previously reported that B. bifidum possesses unique metabolic pathways for O -linked glycans on gastrointestinal mucin (Yoshida E, Sakurama H, Kiyohara M, Nakajima M, Kitaoka M, Ashida H, Hirose J, Katayama T, Yamamoto K, Kumagai H. 2012. Bifidobacterium longum subsp. infantis uses two different β-galactosidases for selectively degrading type-1 and type-2 human milk oligosaccharides. Glycobiology . 22:361–368). The nonreducing termini of O -linked glycans on mucin are frequently covered with histo-blood group antigens. Here, we identified a gene agabb from B. bifidum JCM 1254, which encodes glycoside hydrolase (GH) family 110 α-galactosidase. AgaBb is a 1289-amino acid polypeptide containing an N-terminal signal sequence, a GH110 domain, a carbohydrate-binding module (CBM) 51 domain, a bacterial Ig-like (Big) 2 domain and a C-terminal transmembrane region, in this order. The recombinant enzyme expressed in Escherichia coli hydrolyzed α1,3-linked Gal in branched blood group B antigen [Galα1-3(Fucα1-2)Galβ1-R], but not in a linear xenotransplantation antigen (Galα1-3Galβ1-R). The enzyme also acted on group B human salivary mucin and erythrocytes. We also revealed that CBM51 specifically bound blood group B antigen using both isothermal titration calorimetry and a solid-phase binding assay, and it enhanced the affinity of the enzyme toward substrates with multivalent B antigens. We suggest that this enzyme plays an important role in degrading B antigens to acquire nutrients from mucin oligosaccharides in the gastrointestinal tracts.

Beschreibung: Alg3 of Saccharomyces cerevisiae catalyzes the mannosyl transfer from Man-P-Dol to Man 5 GlcNAc 2 -PP-Dol resulting in the formation of Man 6 GlcNAc 2 -PP-Dol, which is then further processed to the final precursor oligosaccharide Glc 3 Man 9 GlcNAc 2 for N-glycosylation of proteins. Here, we identified the alg3 gene of the mushroom-forming fungus Schizophyllum commune by homology search. Its function was confirmed by the complementation of the alg3 strain of S. cerevisiae . Inactivation of alg3 in S. commune resulted in the production of predominantly Man 3 GlcNAc 2 protein-linked N -glycans. No impact on growth nor a developmental phenotype due to the deletion was observed. This provides a first step toward engineering of a homogeneous, humanized N-glycosylation pattern for the production of therapeutic glycoproteins in mushrooms.

Beschreibung: We previously demonstrated that Siglec-15, a member of the Siglec family of glycan-recognition proteins, is expressed on a subset of macrophages and preferentially recognizes the sialyl-Tn (sTn) antigen, a tumor-associated glycan structure. In this study, we report on the biological significance of the Siglec-15-mediated interaction between monocytes/macrophages and cancer cells. Siglec-15 is expressed on tumor-associated macrophages (TAMs) in various human tumor tissues. We further demonstrated that its expression is substantially elevated in macrophage colony-stimulating factor-induced M2-like macrophages, which produced more transforming growth factor-β (TGF-β) in response to sTn-positive cells than to negative cells. We designed a co-culture model of THP-1 (human monocytic leukemia) cells and H157 (human lung carcinoma) cells mimicking the interaction between monocytes/macrophages and cancer cells that recapitulated the enhanced TGF-β production in Siglec-15 expressing THP-1 cells by the cellular interaction with sTn expressing H157 cells. The enhanced TGF-β production required a direct interaction between the two cell lines through sialic acids. Siglec-15 associates with adaptor protein DNAX activation protein of 12 kDa (DAP12) at the binding determinant Lys 274 in the transmembrane domain and transduces a signal to spleen tyrosine kinase (Syk). The enhanced TGF-β secretion was significantly attenuated by Syk inhibitor treatment of THP-1 cells or by substitution of the Siglec-15 Lys 274 to Ala, which disrupts the molecular interaction between Siglec15 and DAP12. These findings indicate that Siglec-15 recognizes the tumoral sTn antigen and transduces a signal for enhanced TGF-β secretion in TAMs and further suggest that Siglec-15 on macrophages may contribute to tumor progression by the TGF-β-mediated modulation of intratumoral microenvironments.

Beschreibung: Frontonasal dysplasia (FND) refers to a class of midline facial malformations caused by abnormal development of the facial primordia. The term encompasses a spectrum of severities but characteristic features include combinations of ocular hypertelorism, malformations of the nose and forehead and clefting of the facial midline. Several recent studies have drawn attention to the importance of Alx homeobox transcription factors during craniofacial development. Most notably, loss of Alx1 has devastating consequences resulting in severe orofacial clefting and extreme microphthalmia. In contrast, mutations of Alx3 or Alx4 cause milder forms of FND. Whilst Alx1 , Alx3 and Alx4 are all known to be expressed in the facial mesenchyme of vertebrate embryos, little is known about the function of these proteins during development. Here, we report the establishment of a zebrafish model of Alx -related FND. Morpholino knock-down of zebrafish alx1 expression causes a profound craniofacial phenotype including loss of the facial cartilages and defective ocular development. We demonstrate for the first time that Alx1 plays a crucial role in regulating the migration of cranial neural crest (CNC) cells into the frontonasal primordia. Abnormal neural crest migration is coincident with aberrant expression of foxd3 and sox10 , two genes previously suggested to play key roles during neural crest development, including migration, differentiation and the maintenance of progenitor cells. This novel function is specific to Alx1, and likely explains the marked clinical severity of Alx1 mutation within the spectrum of Alx -related FND.

Beschreibung: Activating somatic and germline mutations of closely related RAS genes (H, K, N) have been found in various types of cancer and in patients with developmental disorders, respectively. The involvement of the RAS signalling pathways in developmental disorders has recently emerged as one of the most important drivers in RAS research. In the present study, we investigated the biochemical and cell biological properties of two novel missense KRAS mutations (Y71H and K147E). Both mutations affect residues that are highly conserved within the RAS family. KRAS Y71H showed no clear differences to KRAS wt , except for an increased binding affinity for its major effector, the RAF1 kinase. Consistent with this finding, even though we detected similar levels of active KRAS Y71H when compared with wild-type protein, we observed an increased activation of MEK1/2, irrespective of the stimulation conditions. In contrast, KRAS K147E exhibited a tremendous increase in nucleotide dissociation generating a self-activating RAS protein that can act independently of upstream signals. As a consequence, levels of active KRAS K147E were strongly increased regardless of serum stimulation and similar to the oncogenic KRAS G12V . In spite of this, KRAS K147E downstream signalling did not reach the level triggered by oncogenic KRAS G12V , especially because KRAS K147E was downregulated by RASGAP and moreover exhibited a 2-fold lower affinity for RAF kinase. Here, our findings clearly emphasize that individual RAS mutations, despite being associated with comparable phenotypes of developmental disorders in patients, can cause remarkably diverse biochemical effects with a common outcome, namely a rather moderate gain-of-function.

Beschreibung: Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominantly inherited disorder, which is caused by a pathological expansion of a polyglutamine (polyQ) tract in the coding region of the ATXN2 gene. Like other ataxias, SCA2 most overtly affects Purkinje cells (PCs) in the cerebellum. Using a transgenic mouse model expressing a full-length ATXN2 Q127 -complementary DNA under control of the Pcp2 promoter (a PC-specific promoter), we examined the time course of behavioral, morphologic, biochemical and physiological changes with particular attention to PC firing in the cerebellar slice. Although motor performance began to deteriorate at 8 weeks of age, reductions in PC number were not seen until after 12 weeks. Decreases in the PC firing frequency first showed at 6 weeks and paralleled deterioration of motor performance with progression of disease. Transcription changes in several PC-specific genes such as Calb1 and Pcp2 mirrored the time course of changes in PC physiology with calbindin-28 K changes showing the first small, but significant decreases at 4 weeks. These results emphasize that in this model of SCA2, physiological and behavioral phenotypes precede morphological changes by several weeks and provide a rationale for future studies examining the effects of restoration of firing frequency on motor function and prevention of future loss of PCs.

Beschreibung: Balancing selection has maintained human leukocyte antigen (HLA) allele diversity, but it is unclear whether this selection is symmetric (all heterozygotes are comparable and all homozygotes are comparable in terms of fitness) or asymmetric (distinct heterozygote genotypes display greater fitness than others). We tested the hypothesis that HLA is under asymmetric balancing selection in populations by estimating allelic branch lengths from genetic sequence data encoding peptide-binding domains. Significant deviations indicated changes in the ratio of terminal to internal branch lengths. Such deviations could arise even if no individual alleles present a strikingly altered branch length (e.g. if there is an overall distortion, with all or many terminal branches being longer than expected). DQ and DP loci were also analyzed as haplotypes. Using allele frequencies for 419 distinct populations in 10 geographical regions, we examined population differentiation in alleles within and between regions, and the relationship between allelic branch length and frequency. The strongest evidence for asymmetrical balancing selection was observed for HLA-DRB1 , HLA-B and HLA-DPA1 , with significant deviation ( P ≤ 1.1 x 10 –4 ) in about half of the populations. There were significant results at all loci except HLA-DQB1 / DQA1 . We observed moderate genetic variation within and between geographic regions, similar to the rest of the genome. Branch length was not correlated with allele frequency. In conclusion, sequence data suggest that balancing selection in HLA is asymmetric (some heterozygotes enjoy greater fitness than others). Because HLA polymorphism is crucial for pathogen resistance, this may manifest as a frequency-dependent selection with fluctuation in the fitness of specific heterozygotes over time.

Beschreibung: Birt–Hogg–Dubé syndrome (BHD) is a human cancer disorder caused by mutations in the tumor suppressor gene Folliculin ( FLCN ) with unknown biological functions. Here, we show that the Drosophila homolog of FLCN, dFLCN (a.k.a. dBHD ) localizes to the nucleolus and physically interacts with the 19S proteasomal ATPase, Rpt4, a nucleolar resident and known regulator of rRNA transcription. Downregulation of dFLCN resulted in an increase in nucleolar volume and upregulation of rRNA synthesis, whereas dFLCN overexpression reduced rRNA transcription and counteracted the effects of Rpt4 on rRNA production by preventing the association of Rpt4 with the rDNA locus. We further show that human FLCN exhibited evolutionarily conserved function and that Rpt4 knockdown inhibits the growth of FLCN-deficient human renal cancer cells in mouse xenografts. Our study suggests that FLCN functions as a tumor suppressor by negatively regulating rRNA synthesis.

Beschreibung: KitL, via its receptor cKit, supports primordial germ cell (PGC) growth, survival, migration and reprogramming to pluripotent embryonic germ cells (EGCs). However, the signaling downstream of KitL and its regulation in PGCs remain unclear. A constitutively activating mutation, cKit V558 , causes gain-of-function phenotypes in mast cells and intestines, and gastrointestinal stromal tumors (GISTs) when heterozygous. Unexpectedly, we find that PGC growth is not significantly affected in cKit V558 heterozygotes, whereas in homozygotes, increased apoptosis and inefficient migration lead to the depletion of PGCs. Through genetic studies, we reveal that this oncogenic cKit allele exhibits loss-of-function behavior in PGCs distinct from that in GIST development. Examination of downstream signaling in GISTs from cKit V558/+ mice confirmed hyperphosphorylation of AKT and ERK, but both remain unperturbed in cKit V558/+ PGCs and EGCs. In contrast, we find reduced activation of ERK1/2 and JNK1 in cKit V558 homozygous PGCs and EGCs. Inhibiting JNK, though not ERK1/2, increased apoptosis of wild-type PGCs, but did not further affect the already elevated apoptosis of cKit V558 / V558 PGCs. These results demonstrate a cell-context-dependent response to the cKit V558 mutation. We propose that AKT overload protection and JNK-mediated survival comprise PGC-specific mechanisms for regulating cKit signaling.

Beschreibung: TDP-43 is an evolutionarily conserved RNA-binding protein currently under intense investigation for its involvement in the molecular pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). TDP-43 is normally localized in the nucleus, but translocated to the cytoplasm in diseased neurons. The endogenous functions of TDP-43 in the nervous system remain poorly understood. Here, we show that the loss of Drosophila TDP-43 (dTDP-43) results in an increased production of sensory bristles and sensory organ precursor (SOP) cells on the notum of some but not all flies. The location of ectopic SOPs varies among mutant flies. The penetrance of this novel phenotype is dependent on the gender and sensitive to environmental influences. A similar SOP phenotype was also observed on the wing and in the embryos. Overexpression of dTDP-43 causes both loss and ectopic production of SOPs. Ectopic expression of ALS-associated mutant human TDP-43 (hTDP-43 M337V and hTDP-43 Q331K ) produces a less severe SOP phenotype than hTDP-43 WT , indicating a partial loss of function of mutant hTDP-43. In dTDP-43 mutants, miR-9a expression is significantly reduced. Genetic interaction studies further support the notion that dTDP-43 acts through miR-9a to control the precision of SOP specification. These findings reveal a novel role for endogenous TDP-43 in neuronal specification and suggest that the FTD/ALS-associated RNA-binding protein TDP-43 functions to ensure the robustness of genetic control programs.

Beschreibung: Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most frequent known cause of late-onset Parkinson's disease (PD). To explore the therapeutic potential of small molecules targeting the LRRK2 kinase domain, we characterized two LRRK2 kinase inhibitors, TTT-3002 and LRRK2-IN1, for their effects against LRRK2 activity in vitro and in Caenorhabditis elegans models of LRRK2-linked neurodegeneration. TTT-3002 and LRRK2-IN1 potently inhibited in vitro kinase activity of LRRK2 wild-type and mutant proteins, attenuated phosphorylation of cellular LRRK2 and rescued neurotoxicity of mutant LRRK2 in transfected cells. To establish whether LRRK2 kinase inhibitors can mitigate pathogenesis caused by different mutations including G2019S and R1441C located within and outside of the LRRK2 kinase domain, respectively, we evaluated effects of TTT-3002 and LRRK2-IN1 against R1441C- and G2019S-induced neurodegeneration in C. elegans models. TTT-3002 and LRRK2-IN1 rescued the behavioral deficit characteristic of dopaminergic impairment in transgenic C. elegans expressing human R1441C- and G2019S-LRRK2. The inhibitors displayed nanomolar to low micromolar rescue potency when administered either pre-symptomatically or post-symptomatically, indicating both prevention and reversal of the dopaminergic deficit. The same treatments also led to long-lasting prevention and rescue of neurodegeneration. In contrast, TTT-3002 and LRRK2-IN1 were ineffective against the neurodegenerative phenotype in transgenic worms carrying the inhibitor-resistant A2016T mutation of LRRK2, suggesting that they elicit neuroprotective effects in vivo by targeting LRRK2 specifically. Our findings indicate that the LRRK2 kinase activity is critical for neurodegeneration caused by R1441C and G2019S mutations, suggesting that kinase inhibition of LRRK2 may represent a promising therapeutic strategy for PD.

Beschreibung: Mitochondrial DNA (mtDNA) mutations leading to the disruption of respiratory complex I (CI) have been shown to exhibit anti-tumorigenic effects, at variance with those impairing only the function but not the assembly of the complex, which appear to contribute positively to cancer development. Owing to the challenges in the analysis of the multi-copy mitochondrial genome, it is yet to be determined whether tumour-associated mtDNA lesions occur as somatic modifying factors or as germ-line predisposing elements. Here we investigated the whole mitochondrial genome sequence of 20 pituitary adenomas with oncocytic phenotype and identified pathogenic and/or novel mtDNA mutations in 60% of the cases. Using highly sensitive techniques, namely fluorescent PCR and allele-specific locked nucleic acid quantitative PCR, we identified the most likely somatic nature of these mutations in our sample set, since none of the mutations was detected in the corresponding blood tissue of the patients analysed. Furthermore, we have subjected a series of 48 pituitary adenomas to a high-resolution array comparative genomic hybridization analysis, which revealed that CI disruptive mutations, and the oncocytic phenotype, significantly correlate with low number of chromosomal aberrations in the nuclear genome. We conclude that CI disruptive mutations in pituitary adenomas are somatic modifiers of tumorigenesis most likely contributing not only to the development of oncocytic change, but also to a less aggressive tumour phenotype, as indicated by a stable karyotype.

Beschreibung: Functional loss of SMN1 causes proximal spinal muscular atrophy (SMA), the most common genetic condition accounting for infant lethality. Hence, the hypomorphic copy gene SMN2 is the only resource of functional SMN protein in SMA patients and influences SMA severity in a dose-dependent manner. Consequently, current therapeutic approaches focus on SMN2 . Histone deacetylase inhibitors (HDACi), such as the short chain fatty acid VPA (valproic acid), ameliorate the SMA phenotype by activating the SMN2 expression. By analyzing blood SMN2 expression in 16 VPA-treated SMA patients, about one-third of individuals were identified as positive responders presenting increased SMN2 transcript levels. In 66% of enrolled patients, a concordant response was detected in the respective fibroblasts. Most importantly, by taking the detour of reprograming SMA patients' fibroblasts, we showed that the VPA response was maintained even in GABAergic neurons derived from induced pluripotent stem cells (iPS) cells. Differential expression microarray analysis revealed a complete lack of response to VPA in non-responders, which was associated with an increased expression of the fatty acid translocase CD36. The pivotal role of CD36 as the cause of non-responsiveness was proven in various in vitro approaches. Most importantly, knockdown of CD36 in SMA fibroblasts converted non- into pos-responders. In summary, the concordant response from blood to the central nervous system (CNS) to VPA may allow selection of pos-responders prior to therapy. Increased CD36 expression accounts for VPA non-responsiveness. These findings may be essential not only for SMA but also for other diseases such as epilepsy or migraine frequently treated with VPA.

Beschreibung: Rett syndrome (RTT) is a neurodevelopmental disorder caused primarily by mutations of the X-linked MECP2 gene. Although the loss of MeCP2 function affects many neural systems, impairments of catecholaminergic function have been hypothesized to underlie several of the cardinal behavioral deficits of RTT patients and Mecp2-deficient mice. Although recent Mecp2 reactivation studies indicate that RTT may be a reversible condition, it remains unclear whether specifically preserving Mecp2 function within a specific system will be sufficient to convey beneficial effects. Here, we test whether the selective preservation of Mecp2 within catecholaminergic cells will improve the phenotype of Mecp2-deficient mice. Our results show that this targeted preservation of Mecp2 significantly improves the lifespan, phenotypic severity and cortical epileptiform discharge activity of both male and female Mecp2-deficient mice. Further, we found that the catecholaminergic preservation of Mecp2 also improves the ambulatory rate, rearing activity, motor coordination, anxiety and nest-building performances of Mecp2-deficient mice of each gender. Interestingly, our results also revealed a gender-specific improvement, as specific cortical and hippocampal electroencephalographic abnormalities were significantly improved in male, but not female, rescue mice. Collectively, these results support the role of the catecholaminergic system in the pathogenesis of RTT and provide proof-of-principle that restoring MeCP2 function within this specific system could represent a treatment strategy for RTT.

Beschreibung: Mutations in COL4A1 have been identified in families with hereditary small vessel disease of the brain presumably due to a dominant-negative mechanism. Here, we report on two novel mutations in COL4A1 in two families with porencephaly, intracerebral hemorrhage and severe white matter disease caused by haploinsufficiency. Two families with various clinical presentations of cerebral microangiopathy and autosomal dominant inheritance were examined. Clinical, neuroradiological and genetic investigations were performed. Electron microscopy of the skin was also performed. In one of the families, sequence analysis revealed a one base deletion, c.2085del, leading to a frameshift and a premature stopcodon, p.(Gly696fs). In the other family, a splice site mutation was identified, c.2194-1G〉A, which most likely leads to skipping of an exon with a frameshift and premature termination as a result. In fibroblasts of affected individuals from both the families, nonsense-mediated decay (NMD) of the mutant COL4A1 messenger RNAs (mRNAs) and a clear reduction of COL4A1 protein expression were demonstrated, indicating haploinsufficiency of COL4A1. Moreover, thickening of the capillary basement membrane in the skin was documented, similar to reports in patients with COL4A1 missense mutations. These findings suggest haploinsufficiency, a different mechanism from the commonly assumed dominant-negative effect, for COL4A1 mutations as a cause of (antenatal) intracerebral hemorrhage and white matter disease.

Beschreibung: Motivation: Given the current costs of next-generation sequencing, large studies carry out low-coverage sequencing followed by application of methods that leverage linkage disequilibrium to infer genotypes. We propose a novel method that assumes study samples are sequenced at low coverage and genotyped on a genome-wide microarray, as in the 1000 Genomes Project (1KGP). We assume polymorphic sites have been detected from the sequencing data and that genotype likelihoods are available at these sites. We also assume that the microarray genotypes have been phased to construct a haplotype scaffold. We then phase each polymorphic site using an MCMC algorithm that iteratively updates the unobserved alleles based on the genotype likelihoods at that site and local haplotype information. We use a multivariate normal model to capture both allele frequency and linkage disequilibrium information around each site. When sequencing data are available from trios, Mendelian transmission constraints are easily accommodated into the updates. The method is highly parallelizable, as it analyses one position at a time. Results: We illustrate the performance of the method compared with other methods using data from Phase 1 of the 1KGP in terms of genotype accuracy, phasing accuracy and downstream imputation performance. We show that the haplotype panel we infer in African samples, which was based on a trio-phased scaffold, increases downstream imputation accuracy for rare variants (R2 increases by 〉0.05 for minor allele frequency 〈1%), and this will translate into a boost in power to detect associations. These results highlight the value of incorporating microarray genotypes when calling variants from next-generation sequence data. Availability: The method (called MVNcall) is implemented in a C++ program and is available from http://www.stats.ox.ac.uk/~marchini/#software . Contact: marchini@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results: To align our large (〉80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of 〉50 in mapping speed, aligning to the human genome 550 million 2 x 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80–90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation: STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/ . Contact: dobin@cshl.edu .

Beschreibung: Motivation: Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery. Results: This article introduces the method DLocalMotif that makes use of positional information and negative data for local motif discovery in protein sequences. DLocalMotif combines three scoring functions, measuring degrees of motif over-representation, entropy and spatial confinement, specifically designed to discriminatively exploit the availability of negative data. The method is shown to outperform current methods that use only a subset of these motif characteristics. We apply the method to several biological datasets. The analysis of peroxisomal targeting signals uncovers several novel motifs that occur immediately upstream of the dominant peroxisomal targeting signal-1 signal. The analysis of proline-tyrosine nuclear localization signals uncovers multiple novel motifs that overlap with C2H2 zinc finger domains. We also evaluate the method on classical nuclear localization signals and endoplasmic reticulum retention signals and find that DLocalMotif successfully recovers biologically relevant sequence properties. Availability: http://bioinf.scmb.uq.edu.au/dlocalmotif/ Contact: m.boden@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Much evidence show that over-expression of epidermal growth factor receptor (EGFR) plays an important role in regulating carcinogenesis. Genetic variations in 3' untranslated region (3'UTR) of gene have been reported to affect gene expression by interfering with microRNAs (miRNAs), which are thought to function as either tumour suppressors or oncogenes by binding to their target mRNA. In this study, we investigated the association between the EGFR 3'UTR 774T〉C polymorphism and bladder cancer risk. We used the TaqMan technology to genotype this genetic variant in a hospital-based case–control study of 908 bladder cancer patients and 1239 controls in a Chinese population. We found that the 774CC genotype was associated with a statistically significantly increased risk of bladder cancer [adjusted odds ratio = 1.29, 95% confidence interval = 1.05–1.58], compared with the 774TT/TC genotype, and this increased risk was more pronounced among subgroups of age 〉 65 years, non-smokers and patients’ tumour invasive stage. Furthermore, luciferase assays in T24 cell showed that EGFR 3'UTR 774 T to C substitution could increase the expression of EGFR, which was consistent with the association study finding. Additionally, we also provide evidence that 774T〉C polymorphism increasing EGFR expression was not regulated by hsa-miR-214 binding. These findings suggested that EGFR 3'UTR 774T〉C polymorphism may contribute to susceptibility to bladder cancer.

Beschreibung: Motivation: Protein–protein interaction (PPI) plays an important role in understanding gene functions, and many computational PPI prediction methods have been proposed in recent years. Despite the extensive efforts, PPI prediction still has much room to improve. Sequence-based co-evolution methods include the substitution rate method and the mirror tree method, which compare sequence substitution rates and topological similarity of phylogenetic trees, respectively. Although they have been used to predict PPI in species with small genomes like Escherichia coli , such methods have not been tested in large scale proteome like Homo sapiens . Result: In this study, we propose a novel sequence-based co-evolution method, co-evolutionary divergence (CD), for human PPI prediction. Built on the basic assumption that protein pairs with similar substitution rates are likely to interact with each other, the CD method converts the evolutionary information from 14 species of vertebrates into likelihood ratios and combined them together to infer PPI. We showed that the CD method outperformed the mirror tree method in three independent human PPI datasets by a large margin. With the arrival of more species genome information generated by next generation sequencing, the performance of the CD method can be further improved. Availability: Source code and support are available at http://mib.stat.sinica.edu.tw/LAP/tmp/CD.rar . Contact: syuan@stat.sinica.edu.tw Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : In higher eukaryotes, the identification of translation initiation sites (TISs) has been focused on finding these signals in cDNA or mRNA sequences. Using Arabidopsis thaliana ( A.t. ) information, we developed a prediction tool for signals within genomic sequences of plants that correspond to TISs. Our tool requires only genome sequence, not expressed sequences. Its sensitivity/specificity is for A.t. (90.75%/92.2%), for Vitis vinifera (66.8%/94.4%) and for Populus trichocarpa (81.6%/94.4%), which suggests that our tool can be used in annotation of different plant genomes. We provide a list of features used in our model. Further study of these features may improve our understanding of mechanisms of the translation initiation. Availability and implementation: Our tool is implemented as an artificial neural network. It is available as a web-based tool and, together with the source code, the list of features, and data used for model development, is accessible at http://cbrc.kaust.edu.sa/dts . Contact: vladimir.bajic@kaust.edu.sa Supplementary information : Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Pathway or gene set analysis has been widely applied to genomic data. Many current pathway testing methods use univariate test statistics calculated from individual genomic markers, which ignores the correlations and interactions between candidate markers. Random forests-based pathway analysis is a promising approach for incorporating complex correlation and interaction patterns, but one limitation of previous approaches is that pathways have been considered separately, thus pathway cross-talk information was not considered. Results: In this article, we develop a new pathway hunting algorithm for survival outcomes using random survival forests, which prioritize important pathways by accounting for gene correlation and genomic interactions. We show that the proposed method performs favourably compared with five popular pathway testing methods using both synthetic and real data. We find that the proposed methodology provides an efficient and powerful pathway modelling framework for high-dimensional genomic data. Availability: The R code for the analysis used in this article is available upon request. Contact: xi.steven.chen@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: PacBio sequencers produce two types of characteristic reads (continuous long reads: long and high error rate and circular consensus sequencing: short and low error rate), both of which could be useful for de novo assembly of genomes. Currently, there is no available simulator that targets the specific generation of PacBio libraries. Results: Our analysis of 13 PacBio datasets showed characteristic features of PacBio reads (e.g. the read length of PacBio reads follows a log-normal distribution). We have developed a read simulator, PBSIM, that captures these features using either a model-based or sampling-based method. Using PBSIM, we conducted several hybrid error correction and assembly tests for PacBio reads, suggesting that a continuous long reads coverage depth of at least 15 in combination with a circular consensus sequencing coverage depth of at least 30 achieved extensive assembly results. Availability: PBSIM is freely available from the web under the GNU GPL v2 license ( http://code.google.com/p/pbsim/ ). Contact: mhamada@k.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : Drugster is a fully interactive pipeline designed to break the command line barrier and introduce a new user-friendly environment to perform drug design, lead and structure optimization experiments through an efficient combination of the PDB2PQR, Ligbuilder, Gromacs and Dock suites. Our platform features a novel workflow that guides the user through each logical step of the iterative 3D structural optimization setup and drug design process, by providing a seamless interface to all incorporated packages. Availability: Drugster can be freely downloaded via our dedicated server system at http://www.bioacademy.gr/bioinformatics/drugster/ . Contact: dvlachakis@bioacademy.gr .

Beschreibung: XiP (eXtensible integrative Pipeline) is a flexible, editable and modular environment with a user-friendly interface that does not require previous advanced programming skills to run, construct and edit workflows. XiP allows the construction of workflows by linking components written in both R and Java, the analysis of high-throughput data in grid engine systems and also the development of customized pipelines that can be encapsulated in a package and distributed. XiP already comes with several ready-to-use pipeline flows for the most common genomic and transcriptomic analysis and ~300 computational components. Availability: XiP is open source, freely available under the Lesser General Public License (LGPL) and can be downloaded from http://xip.hgc.jp . Contact: nagasaki@megabank.tohoku.ac.jp

Beschreibung: Existing repositories for experimental datasets typically capture snapshots of data acquired using a single experimental technique and often require manual population and continual curation. We present a storage system for heterogeneous research data that performs dynamic automated indexing to provide powerful search, discovery and collaboration features without the restrictions of a structured repository. ADAM is able to index many commonly used file formats generated by laboratory assays and therefore offers specific advantages to the experimental biology community. However, it is not domain specific and can promote sharing and re-use of working data across scientific disciplines. Availability and implementation: ADAM is implemented using Java and supported on Linux. It is open source under the GNU General Public License v3.0. Installation instructions, binary code, a demo system and virtual machine image and are available at http://www.imperial.ac.uk/bioinfsupport/resources/software/adam . Contact: m.woodbridge@imperial.ac.uk

Beschreibung: : Drug versus Disease (DvD) provides a pipeline, available through R or Cytoscape, for the comparison of drug and disease gene expression profiles from public microarray repositories. Negatively correlated profiles can be used to generate hypotheses of drug-repurposing, whereas positively correlated profiles may be used to infer side effects of drugs. DvD allows users to compare drug and disease signatures with dynamic access to databases Array Express, Gene Expression Omnibus and data from the Connectivity Map. Availability and implementation: R package (submitted to Bioconductor) under GPL 3 and Cytoscape plug-in freely available for download at www.ebi.ac.uk/saezrodriguez/DVD/ . Contact: saezrodriguez@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: RNA-Seq uses the high-throughput sequencing technology to identify and quantify transcriptome at an unprecedented high resolution and low cost. However, RNA-Seq reads are usually not uniformly distributed and biases in RNA-Seq data post great challenges in many applications including transcriptome assembly and the expression level estimation of genes or isoforms. Much effort has been made in the literature to calibrate the expression level estimation from biased RNA-Seq data, but the effect of biases on transcriptome assembly remains largely unexplored. Results: Here, we propose a statistical framework for both transcriptome assembly and isoform expression level estimation from biased RNA-Seq data. Using a quasi-multinomial distribution model, our method is able to capture various types of RNA-Seq biases, including positional, sequencing and mappability biases. Our experimental results on simulated and real RNA-Seq datasets exhibit interesting effects of RNA-Seq biases on both transcriptome assembly and isoform expression level estimation. The advantage of our method is clearly shown in the experimental analysis by its high sensitivity and precision in transcriptome assembly and the high concordance of its estimated expression levels with quantitative reverse transcription–polymerase chain reaction data. Availability: CEM is freely available at http://www.cs.ucr.edu/~liw/cem.html . Contact: liw@cs.ucr.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: A number of studies of individual proteins have shown that post-translational modifications (PTMs) are associated with structural rearrangements of their target proteins. Although such studies provide critical insights into the mechanics behind the dynamic regulation of protein function, they usually feature examples with relatively large conformational changes. However, with the steady growth of Protein Data Bank (PDB) and available PTM sites, it is now possible to more systematically characterize the role of PTMs as conformational switches. In this study, we ask (1) what is the expected extent of structural change upon PTM, (2) how often are those changes in fact substantial, (3) whether the structural impact is spatially localized or global and (4) whether different PTMs have different signatures. Results: We exploit redundancy in PDB and, using root-mean-square deviation, study the conformational heterogeneity of groups of protein structures corresponding to identical sequences in their unmodified and modified forms. We primarily focus on the two most abundant PTMs in PDB, glycosylation and phosphorylation, but show that acetylation and methylation have similar tendencies. Our results provide evidence that PTMs induce conformational changes at both local and global level. However, the proportion of large changes is unexpectedly small; only 7% of glycosylated and 13% of phosphorylated proteins undergo global changes 〉2 Å. Further analysis suggests that phosphorylation stabilizes protein structure by reducing global conformational heterogeneity by 25%. Overall, these results suggest a subtle but common role of allostery in the mechanisms through which PTMs affect regulatory and signaling pathways. Contact: predrag@indiana.edu Supplementary Information : Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Current methods in diagnostic microbiology typically focus on the detection of a single genomic locus or protein in a candidate agent. The presence of the entire microbe is then inferred from this isolated result. Problematically, the presence of recombination in microbial genomes would go undetected unless other genomic loci or protein components were specifically assayed. Microarrays lend themselves well to the detection of multiple loci from a given microbe; furthermore, the inherent nature of microarrays facilitates highly parallel interrogation of multiple microbes. However, none of the existing methods for analyzing diagnostic microarray data has the capacity to specifically identify recombinant microbes. In previous work, we developed a novel algorithm, VIPR, for analyzing diagnostic microarray data. Results: We have expanded upon our previous implementation of VIPR by incorporating a hidden Markov model (HMM) to detect recombinant genomes. We trained our HMM on a set of non-recombinant parental viruses and applied our method to 11 recombinant alphaviruses and 4 recombinant flaviviruses hybridized to a diagnostic microarray in order to evaluate performance of the HMM. VIPR HMM correctly identified 95% of the 62 inter-species recombination breakpoints in the validation set and only two false-positive breakpoints were predicted. This study represents the first description and validation of an algorithm capable of detecting recombinant viruses based on diagnostic microarray hybridization patterns. Availability: VIPR HMM is freely available for academic use and can be downloaded from http://ibridgenetwork.org/wustl/vipr . Contact: davewang@borcim.wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: The boost of next-generation sequencing technologies provides us with an unprecedented opportunity for elucidating genetic mysteries, yet the short-read length hinders us from better assembling the genome from scratch. New protocols now exist that can generate overlapping pair-end reads. By joining the 3' ends of each read pair, one is able to construct longer reads for assembling. However, effectively joining two overlapped pair-end reads remains a challenging task. Result: In this article, we present an efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k -mer frequencies. We evaluated our tool on 30 x simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads. Availability and implementation: COPE is implemented in C++ and is freely available as open-source code at ftp://ftp.genomics.org.cn/pub/cope . Contact: twlam@cs.hku.hk or luoruibang@genomics.org.cn

Beschreibung: Motivation: It becomes widely accepted that human cancer is a disease involving dynamic changes in the genome and that the missense mutations constitute the bulk of human genetic variations. A multitude of computational algorithms, especially the machine learning-based ones, has consequently been proposed to distinguish missense changes that contribute to the cancer progression (‘driver’ mutation) from those that do not (‘passenger’ mutation). However, the existing methods have multifaceted shortcomings, in the sense that they either adopt incomplete feature space or depend on protein structural databases which are usually far from integrated. Results: In this article, we investigated multiple aspects of a missense mutation and identified a novel feature space that well distinguishes cancer-associated driver mutations from passenger ones. An index (DX score) was proposed to evaluate the discriminating capability of each feature, and a subset of these features which ranks top was selected to build the SVM classifier. Cross-validation showed that the classifier trained on our selected features significantly outperforms the existing ones both in precision and robustness. We applied our method to several datasets of missense mutations culled from published database and literature and obtained more reasonable results than previous studies. Availability : The software is available online at http://www.methodisthealth.com/software and https://sites.google.com/site/drivermutationidentification/ . Contact : xzhou@tmhs.org Supplementary information : Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. Results: In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. Availability: The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/ . Contact: zyhe@dlut.edu.cn Supplementary information: Supplementary data are available at Bioinformatics Online.

Beschreibung: Motivation: Methylation of cytosines in DNA is an important epigenetic mechanism involved in transcriptional regulation and preservation of genome integrity in a wide range of eukaryotes. Immunoprecipitation of methylated DNA followed by hybridization to genomic tiling arrays (MeDIP-chip) is a cost-effective and sensitive method for methylome analyses. However, existing bioinformatics methods only enable a binary classification into unmethylated and methylated genomic regions, which limit biological interpretations. Indeed, DNA methylation levels can vary substantially within a given DNA fragment depending on the number and degree of methylated cytosines. Therefore, a method for the identification of more than two methylation states is highly desirable. Results: Here, we present a three-state hidden Markov model (MeDIP-HMM) for analyzing MeDIP-chip data. MeDIP-HMM uses a higher-order state-transition process improving modeling of spatial dependencies between chromosomal regions, allows a simultaneous analysis of replicates and enables a differentiation between unmethylated, methylated and highly methylated genomic regions. We train MeDIP-HMM using a Bayesian Baum–Welch algorithm, integrating prior knowledge on methylation levels. We apply MeDIP-HMM to the analysis of the Arabidopsis root methylome and systematically investigate the benefit of using higher-order HMMs. Moreover, we also perform an in-depth comparison study with existing methods and demonstrate the value of using MeDIP-HMM by comparisons to current knowledge on the Arabidopsis methylome. We find that MeDIP-HMM is a fast and precise method for the analysis of methylome data, enabling the identification of distinct DNA methylation levels. Finally, we provide evidence for the general applicability of MeDIP-HMM by analyzing promoter DNA methylation data obtained for chicken. Availability: MeDIP-HMM is available as part of the open-source Java library Jstacs ( www.jstacs.de/index.php/MeDIP-HMM ). Data files are available from the Jstacs website. Contact: seifert@ipk-gatersleben.de Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Automated annotation of neuroanatomical connectivity statements from the neuroscience literature would enable accessible and large-scale connectivity resources. Unfortunately, the connectivity findings are not formally encoded and occur as natural language text. This hinders aggregation, indexing, searching and integration of the reports. We annotated a set of 1377 abstracts for connectivity relations to facilitate automated extraction of connectivity relationships from neuroscience literature. We tested several baseline measures based on co-occurrence and lexical rules. We compare results from seven machine learning methods adapted from the protein interaction extraction domain that employ part-of-speech, dependency and syntax features. Results: Co-occurrence based methods provided high recall with weak precision. The shallow linguistic kernel recalled 70.1% of the sentence-level connectivity statements at 50.3% precision. Owing to its speed and simplicity, we applied the shallow linguistic kernel to a large set of new abstracts. To evaluate the results, we compared 2688 extracted connections with the Brain Architecture Management System (an existing database of rat connectivity). The extracted connections were connected in the Brain Architecture Management System at a rate of 63.5%, compared with 51.1% for co-occurring brain region pairs. We found that precision increases with the recency and frequency of the extracted relationships. Availability and implementation: The source code, evaluations, documentation and other supplementary materials are available at http://www.chibi.ubc.ca/WhiteText . Contact: paul@chibi.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics Online.

Beschreibung: Motivation: The first step for clinical diagnostics, prognostics and targeted therapeutics of cancer is to comprehensively understand its molecular mechanisms. Large-scale cancer genomics projects are providing a large volume of data about genomic, epigenomic and gene expression aberrations in multiple cancer types. One of the remaining challenges is to identify driver mutations, driver genes and driver pathways promoting cancer proliferation and filter out the unfunctional and passenger ones. Results: In this study, we propose two methods to solve the so-called maximum weight submatrix problem, which is designed to de novo identify mutated driver pathways from mutation data in cancer. The first one is an exact method that can be helpful for assessing other approximate or/and heuristic algorithms. The second one is a stochastic and flexible method that can be employed to incorporate other types of information to improve the first method. Particularly, we propose an integrative model to combine mutation and expression data. We first apply our methods onto simulated data to show their efficiency. We further apply the proposed methods onto several real biological datasets, such as the mutation profiles of 74 head and neck squamous cell carcinomas samples, 90 glioblastoma tumor samples and 313 ovarian carcinoma samples. The gene expression profiles were also considered for the later two data. The results show that our integrative model can identify more biologically relevant gene sets. We have implemented all these methods and made a package called mutated driver pathway finder, which can be easily used for other researchers. Availability: A MATLAB package of MDPFinder is available at http://zhangroup.aporc.org/ShiHuaZhang Contact: zsh@amss.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: Motivation: Biologistics provides data for quantitative analysis of transport (diffusion) processes and their spatio-temporal correlations in cells. Mobility of proteins is one of the few parameters necessary to describe reaction rates for gene regulation. Although understanding of diffusion-limited biochemical reactions in vivo requires mobility data for the largest possible number of proteins in their native forms, currently, there is no database that would contain the complete information about the diffusion coefficients (DCs) of proteins in a given cell type. Results: We demonstrate a method for the determination of in vivo DCs for any molecule—regardless of its molecular weight, size and structure—in any type of cell. We exemplify the method with the database of in vivo DC for all proteins (4302 records) from the proteome of K12 strain of Escherichia coli , together with examples of DC of amino acids, sugars, RNA and DNA. The database follows from the scale-dependent viscosity reference curve (sdVRC). Construction of sdVRC for prokaryotic or eukaryotic cell requires ~20 in vivo measurements using techniques such as fluorescence correlation spectroscopy (FCS), fluorescence recovery after photobleaching (FRAP), nuclear magnetic resonance (NMR) or particle tracking. The shape of the sdVRC would be different for each organism, but the mathematical form of the curve remains the same. The presented method has a high predictive power, as the measurements of DCs of several inert, properly chosen probes in a single cell type allows to determine the DCs of thousands of proteins. Additionally, obtained mobility data allow quantitative study of biochemical interactions in vivo . Contact: rholyst@ichf.edu.pl Supplementary information: Supplementary data are available at Bioinformatics Online.

Beschreibung: Motivation: In modern sequencing studies, one can improve the confidence of genotype calls by phasing haplotypes using information from an external reference panel of fully typed unrelated individuals. However, the computational demands are so high that they prohibit researchers with limited computational resources from haplotyping large-scale sequence data. Results: Our graphics processing unit based software delivers haplotyping and imputation accuracies comparable to competing programs at a fraction of the computational cost and peak memory demand. Availability: Mendel-GPU , our OpenCL software, runs on Linux platforms and is portable across AMD and nVidia GPUs. Users can download both code and documentation at http://code.google.com/p/mendel-gpu/ . Contact: gary.k.chen@usc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : Phylogenetics, likelihood, evolution and complexity ( PLEX ) is a flexible and fast Bayesian Markov chain Monte Carlo software program for large-scale analysis of nucleotide and amino acid data using complex evolutionary models in a phylogenetic framework. The program gains large speed improvements over standard approaches by implementing ‘partial sampling of substitution histories’, a data augmentation approach that can reduce data analysis times from months to minutes on large comparative datasets. A variety of nucleotide and amino acid substitution models are currently implemented, including non-reversible and site-heterogeneous mixture models. Due to efficient algorithms that scale well with data size and model complexity, PLEX can be used to make inferences from hundreds to thousands of taxa in only minutes on a desktop computer. It also performs probabilistic ancestral sequence reconstruction. Future versions will support detection of co-evolutionary interactions between sites, probabilistic tests of convergent evolution and rigorous testing of evolutionary hypotheses in a Bayesian framework. Availability and implementation: PLEX v1.0 is licensed under GPL. Source code and documentation will be available for download at www.evolutionarygenomics.com/ProgramsData/PLEX . PLEX is implemented in C++ and supported on Linux, Mac OS X and other platforms supporting standard C++ compilers. Example data, control files, documentation and accessory Perl scripts are available from the website. Contact: David.Pollock@UCDenver.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : PrIME-DLRS (or colloquially: ‘Delirious’) is a phylogenetic software tool to simultaneously infer and reconcile a gene tree given a species tree. It accounts for duplication and loss events, a relaxed molecular clock and is intended for the study of homologous gene families, for example in a comparative genomics setting involving multiple species. PrIME-DLRS uses a Bayesian MCMC framework, where the input is a known species tree with divergence times and a multiple sequence alignment, and the output is a posterior distribution over gene trees and model parameters. Availability and implementation : PrIME-DLRS is available for Java SE 6+ under the New BSD License, and JAR files and source code can be downloaded from http://code.google.com/p/jprime/ . There is also a slightly older C++ version available as a binary package for Ubuntu, with download instructions at http://prime.sbc.su.se . The C++ source code is available upon request. Contact: joel.sjostrand@scilifelab.se or jens.lagergren@scilifelab.se . Supplementary Information : PrIME-DLRS is based on a sound probabilistic model (Åkerborg et al. , 2009) and has been thoroughly validated on synthetic and biological datasets ( Supplementary Material online ).

Beschreibung: : Computational Structural Biology Toolbox (CSB) is a cross-platform Python class library for reading, storing and analyzing biomolecular structures with rich support for statistical analyses. CSB is designed for reusability and extensibility and comes with a clean, well-documented API following good object-oriented engineering practice. Availability: Stable release packages are available for download from the Python Package Index (PyPI) as well as from the project’s website http://csb.codeplex.com . Contacts: ivan.kalev@gmail.com or michael.habeck@tuebingen.mpg.de

Beschreibung: : GREVE has been developed to assist with the identification of recurrent genomic aberrations across cancer samples. The exact characterization of such aberrations remains a challenge despite the availability of increasing amount of data, from SNParray to next-generation sequencing. Furthermore, genomic aberrations in cancer are especially difficult to handle because they are, by nature, unique to the patients. However, their recurrence in specific regions of the genome has been shown to reflect their relevance in the development of tumors. GREVE makes use of previously characterized events to identify such regions and focus any further analysis. Availability: GREVE is available through a web interface and open-source application ( http://www.well.ox.ac.uk/GREVE ).

Beschreibung: : Protein interaction networks are widely used to depict the relationships between proteins. These networks often lack the information on physical binary interactions, and they do not inform whether there is incompatibility of structure between binding partners. Here, we introduce SAPIN, a framework dedicated to the structural analysis of protein interaction networks. SAPIN first identifies the protein parts that could be involved in the interaction and provides template structures. Next, SAPIN performs structural superimpositions to identify compatible and mutually exclusive interactions. Finally, the results are displayed using Cytoscape Web. Availability: The SAPIN server is available at http://sapin.crg.es . Contact: jae-seong.yang@crg.eu or christina.kiel@crg.eu Supplementary information: Supplementary data are available at Bioinformatics Online.

Beschreibung: : ChemBioServer is a publicly available web application for effectively mining and filtering chemical compounds used in drug discovery. It provides researchers with the ability to (i) browse and visualize compounds along with their properties, (ii) filter chemical compounds for a variety of properties such as steric clashes and toxicity, (iii) apply perfect match substructure search, (iv) cluster compounds according to their physicochemical properties providing representative compounds for each cluster, (v) build custom compound mining pipelines and (vi) quantify through property graphs the top ranking compounds in drug discovery procedures. ChemBioServer allows for pre-processing of compounds prior to an in silico screen, as well as for post-processing of top-ranked molecules resulting from a docking exercise with the aim to increase the efficiency and the quality of compound selection that will pass to the experimental test phase. Availability: The ChemBioServer web application is available at: http://bioserver-3.bioacademy.gr/Bioserver/ChemBioServer/ . Contact: gspyrou@bioacademy.gr

Beschreibung: Motivation: Cell growth and division affect the kinetics of internal cellular processes and the phenotype diversity of cell populations. Since the effects are complex, e.g. different cellular components are partitioned differently in cell division, to account for them in silico, one needs to simulate these processes in great detail. Results : We present SGNS2, a simulator of chemical reaction systems according to the Stochastic Simulation Algorithm with multi-delayed reactions within hierarchical, interlinked compartments which can be created, destroyed and divided at runtime. In division, molecules are randomly segregated into the daughter cells following a specified distribution corresponding to one of several partitioning schemes, applicable on a per-molecule-type basis. We exemplify its use with six models including a stochastic model of the disposal mechanism of unwanted protein aggregates in Escherichia coli , a model of phenotypic diversity in populations with different levels of synchrony, a model of a bacteriophage’s infection of a cell population and a model of prokaryotic gene expression at the nucleotide and codon levels. Availability : SGNS2, instructions and examples available at www.cs.tut.fi/~lloydpri/sgns2/ (open source under New BSD license). Contact : jason.lloyd-price@tut.fi Supplementary information: Supplementary data are available at Bioinformatics online.

Beschreibung: : There is an immediate need for tools to both analyse and visualize in real-time single-nucleotide polymorphisms, insertions and deletions, and other structural variants from new sequence file formats. We have developed VarB software that can be used to visualize variant call format files in real time, as well as identify regions under balancing selection and informative markers to differentiate user-defined groups (e.g. populations). We demonstrate its utility using sequence data from 50 Plasmodium falciparum isolates comprising two different continents and confirm known signals from genomic regions that contain important antigenic and anti-malarial drug-resistance genes. Availability and implementation: The C++-based software VarB and user manual are available from www.pathogenseq.org/varb . Contact: taane.clark@lshtm.ac.uk

Beschreibung: : comb-p is a command-line tool and a python library that manipulates BED files of possibly irregularly spaced P -values and (1) calculates auto-correlation, (2) combines adjacent P -values, (3) performs false discovery adjustment, (4) finds regions of enrichment (i.e. series of adjacent low P -values) and (5) assigns significance to those regions. In addition, tools are provided for visualization and assessment. We provide validation and example uses on bisulfite-seq with P -values from Fisher’s exact test, tiled methylation probes using a linear model and Dam-ID for chromatin binding using moderated t -statistics. Because the library accepts input in a simple, standardized format and is unaffected by the origin of the P -values, it can be used for a wide variety of applications. Availability: comb-p is maintained under the BSD license. The documentation and implementation are available at https://github.com/brentp/combined-pvalues . Contact: bpederse@gmail.com

Beschreibung: : ImgLib2 is an open-source Java library for n -dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins. Availability : ImgLib2 is licensed under BSD. Documentation and source code are available at http://imglib2.net and in a public repository at https://github.com/imagej/imglib . Supplementary Information: Supplementary data are available at Bioinformatics Online. Contact : saalfeld@mpi-cbg.de

Beschreibung: : We have established an RNA mapping database (RMDB) to enable structural, thermodynamic and kinetic comparisons across single-nucleotide-resolution RNA structure mapping experiments. The volume of structure mapping data has greatly increased since the development of high-throughput sequencing techniques, accelerated software pipelines and large-scale mutagenesis. For scientists wishing to infer relationships between RNA sequence/structure and these mapping data, there is a need for a database that is curated, tagged with error estimates and interfaced with tools for sharing, visualization, search and meta-analysis. Through its on-line front-end, the RMDB allows users to explore single-nucleotide-resolution mapping data in heat-map, bar-graph and colored secondary structure graphics; to leverage these data to generate secondary structure hypotheses; and to download the data in standardized and computer-friendly files, including the RDAT and community-consensus SNRNASM formats. At the time of writing, the database houses 53 entries, describing more than 2848 experiments of 1098 RNA constructs in several solution conditions and is growing rapidly. Availability: Freely available on the web at http://rmdb.stanford.edu Contact: rhiju@stanford.edu Supplementary information: Supplementary data are available at Bioinformatics Online.

Beschreibung: : Spoligotyping is a well-established genotyping technique based on the presence of unique DNA sequences in Mycobacterium tuberculosis ( Mtb ), the causal agent of tuberculosis disease (TB). Although advances in sequencing technologies are leading to whole-genome bacterial characterization, tens of thousands of isolates have been spoligotyped, giving a global view of Mtb strain diversity. To bridge the gap, we have developed SpolPred , a software to predict the spoligotype from raw sequence reads. Our approach is compared with experimentally and de novo assembly determined strain types in a set of 44 Mtb isolates. In silico and experimental results are identical for almost all isolates (39/44). However, SpolPred detected five experimentally false spoligotypes and was more accurate and faster than the assembling strategy. Application of SpolPred to an additional seven isolates with no laboratory data led to types that clustered with identical experimental types in a phylogenetic analysis using single-nucleotide polymorphisms. Our results demonstrate the usefulness of the tool and its role in revealing experimental limitations. Availability and implementation : SpolPred is written in C and is available from www.pathogenseq.org/spolpred . Contact: francesc.coll@lshtm.ac.uk Supplementary information: Supplementary data are available at Bioinformatics Online.

Beschreibung: : NetworkView is an application for the display and analysis of protein·RNA interaction networks derived from structure and/or dynamics. These networks typically model individual protein residues and nucleic acid monomers as nodes and their pairwise contacts as edges with associated weights. NetworkView projects the network onto the underlying 3D molecular structure so that visualization and analysis of the network can be coupled to physical and biological properties. NetworkView is implemented as a plugin to the molecular visualization software VMD. Availability and implementation : NetworkView is included with VMD, which is available at http://www.ks.uiuc.edu/Research/vmd/ . Documentation, tutorials and supporting programs are available at http://www.scs.illinois.edu/schulten/software/ . Contact : networkview@scs.illinois.edu

Beschreibung: In a matched observational study of treatment effects, a sensitivity analysis asks about the magnitude of the departure from random assignment that would need to be present to alter the conclusions of an analysis that assumes that matching for measured covariates removes all bias. The reported degree of sensitivity to unmeasured biases depends on both the process that generated the data and the chosen methods of analysis, so a poor choice of method may lead to an exaggerated report of sensitivity to bias. This suggests the possibility of performing more than one analysis with a correction for multiple inference, say testing one null hypothesis using two or three different tests. In theory and in an example, it is shown that, in large samples, the gains from testing twice will often be large, because testing twice has the larger of the two design sensitivities of the component tests, and the losses due to correcting for two tests will often be small, because two tests of one hypothesis will typically be highly correlated, so a correction for multiple testing that takes this into account will be small. An illustration uses data from the U.S. National Health and Nutrition Examination Survey concerning lead in the blood of cigarette smokers.

Beschreibung: Inferences related to the second-order properties of functional data, as expressed by covariance structure, can become unreliable when the data are non-Gaussian or contain unusual observations. In the functional setting, it is often difficult to identify atypical observations, as their distinguishing characteristics can be manifold but subtle. In this paper, we introduce the notion of a dispersion operator, investigate its use in probing the second-order structure of functional data, and develop a test for comparing the second-order characteristics of two functional samples that is resistant to atypical observations and departures from normality. The proposed test is a regularized M -test based on a spectrally truncated version of the Hilbert–Schmidt norm of a score operator defined via the dispersion operator. We derive the asymptotic distribution of the test statistic, investigate the behaviour of the test in a simulation study and illustrate the method on a structural biology dataset.

Beschreibung: Linear classifiers are very popular, but can have limitations when classes have distinct subpopulations. General nonlinear kernel classifiers are very flexible, but do not give clear interpretations and may not be efficient in high dimensions. We propose the bidirectional discrimination classification method, which generalizes linear classifiers to two or more hyperplanes. This new family of classification methods gives much of the flexibility of a general nonlinear classifier while maintaining the interpretability, and much of the parsimony, of linear classifiers. They provide a new visualization tool for high-dimensional, low-sample-size data. Although the idea is generally applicable, we focus on the generalization of the support vector machine and distance-weighted discrimination methods. The performance and usefulness of the proposed method are assessed using asymptotics and demonstrated through analysis of simulated and real data. Our method leads to better classification performance in high-dimensional situations where subclusters are present in the data.

Beschreibung: Two transformations are proposed that give orthogonal components with a one-to-one correspondence between the original vectors and the components. The aim is that each component should be close to the vector with which it is paired, orthogonality imposing a constraint. The transformations lead to a variety of new statistical methods, including a unified approach to the identification and diagnosis of collinearities, a method of setting prior weights for Bayesian model averaging, and a means of calculating an upper bound for a multivariate Chebychev inequality. One transformation has the property that duplicating a vector has no effect on the orthogonal components that correspond to nonduplicated vectors, and is determined using a new algorithm that also provides the decomposition of a positive-definite matrix in terms of a diagonal matrix and a correlation matrix. The algorithm is shown to converge to a global optimum.

Beschreibung: Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the noise level via the mean residual square and scaling the penalty in proportion to the estimated noise level. The iterative algorithm costs little beyond the computation of a path or grid of the sparse regression estimator for penalty levels above a proper threshold. For the scaled lasso, the algorithm is a gradient descent in a convex minimization of a penalized joint loss function for the regression coefficients and noise level. Under mild regularity conditions, we prove that the scaled lasso simultaneously yields an estimator for the noise level and an estimated coefficient vector satisfying certain oracle inequalities for prediction, the estimation of the noise level and the regression coefficients. These inequalities provide sufficient conditions for the consistency and asymptotic normality of the noise-level estimator, including certain cases where the number of variables is of greater order than the sample size. Parallel results are provided for least-squares estimation after model selection by the scaled lasso. Numerical results demonstrate the superior performance of the proposed methods over an earlier proposal of joint convex minimization.

Beschreibung: In this article, we propose a regression method for simultaneous supervised clustering and feature selection over a given undirected graph, where homogeneous groups or clusters are estimated as well as informative predictors, with each predictor corresponding to one node in the graph and a connecting path indicating a priori possible grouping among the corresponding predictors. The method seeks a parsimonious model with high predictive power through identifying and collapsing homogeneous groups of regression coefficients. To address computational challenges, we present an efficient algorithm integrating the augmented Lagrange multipliers, coordinate descent and difference convex methods. We prove that the proposed method not only identifies the true homogeneous groups and informative features consistently but also leads to accurate parameter estimation. A gene network dataset is analysed to demonstrate that the method can make a difference by exploring dependency structures among the genes.

Beschreibung: This article proposes a method of moments technique for estimating the sparsity of signals in a random sample. This involves estimating the largest eigenvalue of a large Hermitian trigonometric matrix under mild conditions. As illustration, the method is applied to two well-known problems. The first focuses on the sparsity of a large covariance matrix and the second investigates the sparsity of a sequence of signals observed with stationary, weakly dependent noise. Simulation shows that the proposed estimators can have significantly smaller mean absolute errors than their main competitors.

Beschreibung: We introduce a doubly stochastic marked point process model for supervised classification problems. Regardless of the number of classes or the dimension of the feature space, the model requires only 2–3 parameters for the covariance function. The classification criterion involves a permanental ratio for which an approximation using a polynomial-time cyclic expansion is proposed. The approximation is effective even if the feature region occupied by one class is a patchwork interlaced with regions occupied by other classes. An application to DNA microarray analysis indicates that the cyclic approximation is effective even for high-dimensional data. It can employ feature variables in an efficient way to reduce the prediction error significantly. This is critical when the true classification relies on nonreducible high-dimensional features.

Beschreibung: Researchers in the biological sciences nowadays often encounter the curse of dimensionality. To tackle this, sufficient dimension reduction aims to estimate the central subspace, in which all the necessary information supplied by the covariates regarding the response of interest is contained. Subsequent statistical analysis can then be made in a lower-dimensional space while preserving relevant information. Many studies are concerned with the transformed response rather than the original one, but they may have different central subspaces. When estimating the central subspace of the transformed response, direct methods will be inefficient. In this article, we propose a more efficient two-stage estimator of the central subspace of a transformed response. This approach is extended to censored responses and is applied to combining multiple biomarkers. Simulation studies and data examples support the superiority of the procedure.

Beschreibung: Transient semi-Markov processes have traditionally been used to describe the transitions of a patient through the various states of a multistate survival model. A survival distribution in this context is a sojourn through the states until passage to a fatal absorbing state or certain endpoint states. Using complete sojourn data, this paper shows how such survival distributions and associated hazard functions can be estimated nonparametrically and also how nonparametric bootstrap pointwise confidence bands can be constructed for them when patients are subject to independent right censoring from each state during the sojourn. Limitations to the estimability of such survival distributions that result from random censoring with bounded support are clarified. The methods are applicable to any sort of sojourn through any finite state process of arbitrary complexity involving feedback into previously occupied states.

Beschreibung: In some problems involving functional data, it is desired to undertake prediction or classification before the full trajectory of a function is observed. In such cases, it is often preferable to suffer somewhat greater error in return for making a decision relatively early. The prediction and classification problems can be treated similarly, using mean squared prediction error, or classification error, respectively, as the means for quantifying performance, so in this paper we focus principally on classification. We introduce a method for determining when an early decision can reasonably be made, using only part of the trajectory, and we show how to use the method to choose among data types. Our approach is fully nonparametric, and no specific model is required. Properties of error-rate are studied as functions of time and data type. The effectiveness of the proposed method is illustrated in both theoretical and numerical terms. The classification referred to in this paper would be termed supervised classification in machine learning, to distinguish it from unsupervised classification, or clustering.

Beschreibung: Linear mixed models cover a wide range of statistical methods, which have found many uses in the estimation for complex surveys. The purpose of this work is to consider methods by which linear mixed models may be used at the design stage of a survey to incorporate available auxiliary information. This paper reviews the ideas of balanced sampling and the cube algorithm, and proposes an implementation of the latter by which penalized balanced samples can be selected. Such samples can reduce or eliminate the need for linear mixed model weight adjustments, a result demonstrated theoretically and via simulation. Horvitz–Thompson estimators for such samples will be highly efficient for any responses well approximated by a linear mixed model in the auxiliary information. In Monte Carlo experiments using nonparametric and temporal linear mixed models, the strategy of penalized balanced sampling with Horvitz–Thompson estimation dominates a variety of standard strategies.

Beschreibung: Monte Carlo algorithms are commonly used to identify a set of models for Bayesian model selection or model averaging. Because empirical frequencies of models are often zero or one in high-dimensional problems, posterior probabilities calculated from the observed marginal likelihoods, renormalized over the sampled models, are often employed. Such estimates are the only recourse in several newer stochastic search algorithms. In this paper, we prove that renormalization of posterior probabilities over the set of sampled models generally leads to bias that may dominate mean squared error. Viewing the model space as a finite population, we propose a new estimator based on a ratio of Horvitz–Thompson estimators that incorporates observed marginal likelihoods, but is approximately unbiased. This is shown to lead to a reduction in mean squared error compared to the empirical or renormalized estimators, with little increase in computational cost.

Beschreibung: Many proper scoring rules such as the Brier and log scoring rules implicitly reward a probability forecaster relative to a uniform baseline distribution. Recent work has motivated weighted proper scoring rules, which have an additional baseline parameter. To date two families of weighted proper scoring rules have been introduced, the weighted power and pseudospherical scoring families. These families are compatible with the log scoring rule: when the baseline maximizes the log scoring rule over some set of distributions, the baseline also maximizes the weighted power and pseudospherical scoring rules over the same set. We characterize all weighted proper scoring families and prove a general property: every proper scoring rule is compatible with some weighted scoring family, and every weighted scoring family is compatible with some proper scoring rule.

Beschreibung: Projective shape consists of the information about a configuration of points that is invariant under projective transformations. It is an important tool in machine vision to pick out features that are invariant to the choice of camera view. The simplest example is the cross ratio for a set of four collinear points. Recent work involving ideas from multivariate robustness enables us to introduce here a natural preshape on projective shape space. This makes it possible to adapt the Procrustes analysis that forms the basis of much methodology in the simpler setting of similarity shape space.