ALBERT

Description: The dihedral angle formed at junctions between two plagioclase grains and a grain of augite is only very rarely in textural equilibrium in gabbros from kilometre-scale crustal layered intrusions. The median of a population of these disequilibrium angles, cpp , varies systematically within a single layered intrusion, remaining constant over large stretches of stratigraphy with significant increases and decreases associated with the addition or reduction respectively of the number of phases on the liquidus of the bulk magma. The stepwise changes in cpp are present in the Upper Zone of the Bushveld Complex, the Megacyclic Unit I of the Sept Iles Intrusion, and the Layered Series of the Skaergaard intrusion. The plagioclase-bearing cumulates of Rum have a bimodal distribution of cpp , dependent on whether the cumulus assemblage includes clinopyroxene. The presence of the stepwise changes is independent of the order of arrival of cumulus phases and of the composition of either the cumulus phases or the inferred composition of the interstitial liquid. The only parameter that behaves in an exactly analogous manner to cpp is the rate of change in enthalpy with temperature ( H / T ) during crystallization. Both H / T and cpp increase with the addition of a liquidus phase, and decrease with the removal of a liquidus phase. The replacement of one phase by another has little effect on H / T and no discernible effect on cpp . An increase of H / T results in an increase in the fraction of the total enthalpy budget that is the latent heat of crystallization (the fractional latent heat). It also increases the mass crystallized in each incremental temperature drop (the crystal productivity). These increases of both fractional latent heat and crystal productivity are likely to cause an increase in the time taken to form three-grain junctions in the mush via thermal buffering of a thickened mushy layer. We suggest these are the underlying causes of stepwise increases in cpp . Stepwise changes in the geometry of three-grain junctions in fully solidified gabbros thus provide a clear microstructural marker for the progress of fractionation down the liquid line of descent in layered intrusions.

Description: High-resolution sampling in monogenetic fields has the potential to reveal fine-scale heterogeneity of the mantle, a feature that may be overwhelmed by larger fluxes of magma, or missed by under-sampling. The Quaternary Auckland Volcanic Field (AVF) in northern New Zealand is a basaltic field of 51 small-volume volcanic centres, and is one of the best-sampled examples of a monogenetic volcanic field. We present data for 12 centres in the volcanic field. These show the large compositional variations between volcanoes as well as through single eruptive sequences. Whole-rock compositions range from subalkaline basalt in the larger centres, through alkali basalt to nephelinite in the smallest centres. Fractional crystallization has had a limited effect in many of the centres, but high-pressure clinopyroxene crystallization may have occurred in others. Three end-members are observed in Pb isotope space, indicating that distinct mantle source components are involved in the petrogenesis of the magmas. Whole-rock multi-element patterns show that the larger centres have prominent positive Sr anomalies and lack K anomalies, whereas the smaller centres have prominent negative K anomalies and lack Sr anomalies. The melting parameters and compositions of the sources involved are modelled using trace element ratios and multi-element patterns, and three components are characterized: (1) fertile peridotite with a Pb-isotope composition similar to Pacific mid-ocean ridge basalt; (2) eclogite domains with a HIMU-like isotope composition dispersed within the fertile peridotite; (3) slightly depleted subduction-metasomatized peridotitic lithospheric mantle (containing c . 3% subduction fluids). Modelling shows that melting in the AVF begins in garnet-bearing fertile asthenosphere (with preferential melting of eclogite domains) and that melts are variably diluted by melts of the lithospheric source. The U–Th isotope compositions of the end-members in the AVF show 230 Th excess [( 230 Th/ 232 Th) ratios of 1·11–1·38], with the samples of lower ( 230 Th/ 232 Th) exhibiting higher ( 238 U/ 232 Th), which we attribute to the dilution effect of the melts from the lithospheric mantle source. Modelling reveals a correlation between melting in the asthenosphere, the degree of melting and incorporation of the metasomatized lithospheric mantle source, and the resultant size of the volcanic centre. This suggests that the scale of the eruption may essentially be controlled by asthenospheric mantle dynamics.

Description: The origin of mafic and ultramafic sills exhibiting different whole-rock compositional profiles (e.g. I-, C-, D-, M- and S-shaped profiles) remains controversial. We have addressed this issue by revisiting three ~100 m thick Siberian dolerite sills (Vavukansky, Kuz’movsky and Vilyuysky) that display remarkable internal differentiation. The Vavukansky sill has an M-shaped profile with prominent basal and top reversals showing inward increases in whole-rock MgO, Mg-number [100Mg/(Mg + Fe)] and normative An content [100An/(An + Ab)], followed by the Layered and Upper Border Series with inward decreases in these indices. The Kuz’movsky and Vilyuysky sills both show S-shaped profiles similar to the Vavukansky sill, but lack a top reversal. These whole-rock M- and S-shaped profiles are accompanied by similar profiles in mineral compositions. Plagioclase and, to a lesser extent, olivine show systematic inward increases in An content and Mg-number, respectively, across basal and top reversals. These compositional trends are followed by inward decreases in these ratios in the interiors of the Vavukansky and Kuz’movsky sills. Currently accepted models attribute whole-rock M- and S-shaped compositional profiles to crystal settling, compositional convection or compaction operating in closed systems. Our observations challenge these traditional interpretations because variations in mineral compositions observed in marginal reversals cannot result from closed-system fractionation. We suggest instead that initially the sills evolved as open systems that were slowly inflated by magmas that became gradually more primitive with time. The inflation was accompanied by in situ crystallization that preserved the preceding fractionation history of the injected magmas by forming basal and top reversals with minerals becoming more primitive inwards. This process culminated with rapid inflation of the sills to their current size owing to a major influx of primitive magma. Subsequently, magma flow through the sills ceased and they evolved as closed systems by fractional crystallization. This resulted in the Layered and Upper Border Series with minerals becoming more evolved inwards. This model can be extended to explain other compositional profiles and petrological features in mafic and ultramafic sills.

Description: Motivation: Pyrosequencing technology provides an important new approach to more extensively characterize diverse sequence populations and detect low frequency variants. However, the promise of this technology has been difficult to realize, as careful correction of sequencing errors is crucial to distinguish rare variants (~1%) in an infected host with high sensitivity and specificity. Results: We developed a new approach, referred to as Indel and Carryforward Correction (ICC), to cluster sequences without substitutions and locally correct only indel and carryforward sequencing errors within clusters to ensure that no rare variants are lost. ICC performs sequence clustering in the order of (i) homopolymer indel patterns only, (ii) indel patterns only and (iii) carryforward errors only, without the requirement of a distance cutoff value. Overall, ICC removed 93–95% of sequencing errors found in control datasets. On pyrosequencing data from a PCR fragment derived from 15 HIV-1 plasmid clones mixed at various frequencies as low as 0.1%, ICC achieved the highest sensitivity and similar specificity compared with other commonly used error correction and variant calling algorithms. Availability and implementation: Source code is freely available for download at http://indra.mullins.microbiol.washington.edu/ICC . It is implemented in Perl and supported on Linux, Mac OS X and MS Windows. Contact: jmullins@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Tiki proteins appear to antagonize Wnt signalling pathway by acting as Wnt proteases, thereby affecting Wnt solubility by its amino-terminal cleavage. Tiki1 protease activity was shown to be metal ion-dependent and was inhibited by chelating agents and thus was tentatively proposed to be a metalloprotease. Nevertheless, Tiki proteins exhibit no detectable sequence similarity to previously described metalloproteases, but instead have been reported as being homologues of TraB proteins (Pfam ID: PF01963), a widely distributed family of unknown function and structure. Here, we show that Tiki proteins are members of a new superfamily of domains contained not just in TraB proteins, but also in erythromycin esterase (Pfam ID: PF05139), DUF399 (domain of unknown function 399; Pfam ID: PF04187) and MARTX toxins that contribute to host invasion and pathogenesis by bacteria. We establish the core fold of this enzymatic domain and its catalytic residues. Contact: luis.sanchezpulido@dpag.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The research area metabolomics achieved tremendous popularity and development in the last couple of years. Owing to its unique interdisciplinarity, it requires to combine knowledge from various scientific disciplines. Advances in the high-throughput technology and the consequently growing quality and quantity of data put new demands on applied analytical and computational methods. Exploration of finally generated and analyzed datasets furthermore relies on powerful tools for data mining and visualization. Results: To cover and keep up with these requirements, we have created MeltDB 2.0, a next-generation web application addressing storage, sharing, standardization, integration and analysis of metabolomics experiments. New features improve both efficiency and effectivity of the entire processing pipeline of chromatographic raw data from pre-processing to the derivation of new biological knowledge. First, the generation of high-quality metabolic datasets has been vastly simplified. Second, the new statistics tool box allows to investigate these datasets according to a wide spectrum of scientific and explorative questions. Availability: The system is publicly available at https://meltdb.cebitec.uni-bielefeld.de . A login is required but freely available. Contact: nkessler@cebitec.uni-bielefeld.de

Description: Motivation: High - throughput next - generation sequencing technologies enable increasingly fast and affordable sequencing of genomes and transcriptomes, with a broad range of applications. The quality of the sequencing data is crucial for all applications. A significant portion of the data produced contains errors, and ever more efficient error correction programs are needed. Results: We propose RACER (Rapid and Accurate Correction of Errors in Reads), a new software program for correcting errors in sequencing data. RACER has better error-correcting performance than existing programs, is faster and requires less memory. To support our claims, we performed extensive comparison with the existing leading programs on a variety of real datasets. Availability: RACER is freely available for non-commercial use at www.csd.uwo.ca/~ilie/RACER/ . Contact: ilie@csd.uwo.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Interactions between various types of molecules that regulate crucial cellular processes are extensively investigated by high-throughput experiments and require dedicated computational methods for the analysis of the resulting data. In many cases, these data can be represented as a bipartite graph because it describes interactions between elements of two different types such as the influence of different experimental conditions on cellular variables or the direct interaction between receptors and their activators/inhibitors. One of the major challenges in the analysis of such noisy datasets is the statistical evaluation of the relationship between any two elements of the same type. Here, we present SICOP (significant co-interaction patterns), an implementation of a method that provides such an evaluation based on the number of their common interaction partners, their so-called co-interaction. This general network analytic method, proved successful in diverse fields, provides a framework for assessing the significance of this relationship by comparison with the expected co-interaction in a suitable null model of the same bipartite graph. SICOP takes into consideration up to two distinct types of interactions such as up- or downregulation. The tool is written in Java and accepts several common input formats and supports different output formats, facilitating further analysis and visualization. Its key features include a user-friendly interface, easy installation and platform independence. Availability: The software is open source and available at cna.cs.uni-kl.de/SICOP under the terms of the GNU General Public Licence (version 3 or later). Contact: agnes.horvat@iwr.uni-heidelberg.de or zweig@cs.uni-kl.de

Description: : Molecular recognition features (MoRFs) are small, intrinsically disordered regions in proteins that undergo a disorder-to-order transition on binding to their partners. MoRFs are involved in protein–protein interactions and may function as the initial step in molecular recognition. The aim of this work was to collect, organize and store all membrane proteins that contain MoRFs. Membrane proteins constitute ~30% of fully sequenced proteomes and are responsible for a wide variety of cellular functions. MoRFs were classified according to their secondary structure, after interacting with their partners. We identified MoRFs in transmembrane and peripheral membrane proteins. The position of transmembrane protein MoRFs was determined in relation to a protein’s topology. All information was stored in a publicly available mySQL database with a user-friendly web interface. A Jmol applet is integrated for visualization of the structures. mpMoRFsDB provides valuable information related to disorder-based protein–protein interactions in membrane proteins. Availability: http://bioinformatics.biol.uoa.gr/mpMoRFsDB Contact: shamodr@biol.uoa.gr

Description: : The signaling Petri net (SPN) simulator, designed to provide insights into the trends of molecules’ activity levels in response to an external stimulus, contributes to the systems biology necessity of analyzing the dynamics of large-scale cellular networks. Implemented into the freely available software, BioLayout Express 3D , the simulator is publicly available and easy to use, provided the input files are prepared in the GraphML format, typically using the network editing software, yEd, and standards specific to the software. However, analysis of complex networks represented using other systems biology formatting languages (on which popular software, such as CellDesigner and Cytoscape, are based) requires manual manipulation, a step that is prone to error and limits the use of the SPN simulator in BioLayout Express 3D . To overcome this, we present a Cytoscape plug-in that enables users to automatically convert networks for analysis with the SPN simulator from the standard systems biology markup language. The automation of this step opens the SPN simulator to a far larger user group than has previously been possible. Availability and implementation: Distributed under the GNU General Public License Version 3 at http://apps.cytoscape.org/apps/spnconverter . Contact: christine@picb.ac.cn

Description: Motivation: Conformational diversity is a key concept in the understanding of different issues related with protein function such as the study of catalytic processes in enzymes, protein-protein recognition, protein evolution and the origins of new biological functions. Here, we present a database of proteins with different degrees of conformational diversity. Conformational Diversity of Native State (CoDNaS) is a redundant collection of three-dimensional structures for the same protein derived from protein data bank. Structures for the same protein obtained under different crystallographic conditions have been associated with snapshots of protein dynamism and consequently could characterize protein conformers. CoDNaS allows the user to explore global and local structural differences among conformers as a function of different parameters such as presence of ligand, post-translational modifications, changes in oligomeric states and differences in pH and temperature. Additionally, CoDNaS contains information about protein taxonomy and function, disorder level and structural classification offering useful information to explore the underlying mechanism of conformational diversity and its close relationship with protein function. Currently, CoDNaS has 122 122 structures integrating 12 684 entries, with an average of 9.63 conformers per protein. Availability: The database is freely available at http://www.codnas.com.ar/ . Contact: gusparisi@gmail.com

Description: Motivation: Recent experimental advancements allow determining positions of nucleosomes for complete genomes. However, the resulting nucleosome occupancy maps are averages of heterogeneous cell populations. Accordingly, they represent a snapshot of a dynamic ensemble at a single time point with an overlay of many configurations from different cells. To study the organization of nucleosomes along the genome and to understand the mechanisms of nucleosome translocation, it is necessary to retrieve features of specific conformations from the population average. Results: Here, we present a method for identifying non-overlapping nucleosome configurations that combines binary-variable analysis and a Monte Carlo approach with a simulated annealing scheme. In this manner, we obtain specific nucleosome configurations and optimized solutions for the complex positioning patterns from experimental data. We apply the method to compare nucleosome positioning at transcription factor binding sites in different mouse cell types. Our method can model nucleosome translocations at regulatory genomic elements and generate configurations for simulations of the spatial folding of the nucleosome chain. Availability: Source code, precompiled binaries, test data and a web-based test installation are freely available at http://bioinformatics.fh-stralsund.de/nucpos/ Contact: gero.wedemann@fh-stralsund.de Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: We show the existence and uniqueness of a solution for the nonlocal vector-valued Allen–Cahn variational inequality in a formulation involving Lagrange multipliers for local and nonlocal constraints. Furthermore, we propose and analyse a primal–dual active set (PDAS) method for local and nonlocal vector-valued Allen–Cahn variational inequalities. The local convergence behaviour of the PDAS algorithm is studied by interpreting the approach as a semismooth Newton method and numerical simulations are presented demonstrating its efficiency.

Description: In this paper, we will present a generalized convolution quadrature for solving linear parabolic and hyperbolic evolution equations. The original convolution quadrature method by Lubich works very nicely for equidistant time steps while the generalization of the method and its analysis to nonuniform time stepping is by no means obvious. We will introduce the generalized convolution quadrature allowing for variable time steps and develop a theory for its error analysis. This method opens the door for further development towards adaptive time stepping for evolution equations. As the main application of our new theory, we will consider the wave equation in exterior domains which is formulated as a retarded boundary integral equation.

Description: We address the error control of Galerkin discretization (in space) of linear second-order hyperbolic problems. More specifically, we derive a posteriori error bounds in the L ( L 2 ) norm for finite element methods for the linear wave equation, under minimal regularity assumptions. The theory is developed for both the space-discrete case and for an implicit fully discrete scheme. The derivation of these bounds relies crucially on carefully constructed space and time reconstructions of the discrete numerical solutions, in conjunction with a technique introduced by Baker (1976, Error estimates for finite element methods for second-order hyperbolic equations. SIAM J. Numer. Anal. , 13 , 564–576) in the context of a priori error analysis of Galerkin discretization of the wave problem in weaker-than-energy spatial norms.

Description: The surface finite element method can be used to approximate curvatures on embedded hypersurfaces and to discretize geometric partial differential equations. In this paper, we present a definition of discrete Ricci curvature on polyhedral hypersurfaces of arbitrary dimension based on the discretization of a weak formulation with isoparametric finite elements. We prove that for a piecewise quadratic approximation of a two- or three-dimensional hypersurface R n +1 , this definition approximates the Ricci curvature of with a linear order of convergence in the L 2 ( ) norm. By using a smoothing scheme in the case of a piecewise linear approximation of , we still get a convergence of order 2/3 in the L 2 ( ) norm and of order 1/3 in the W 1, 2 ( ) norm.

Description: We give general conditions which guarantee that the sequence generated by a descent algorithm converges to an equilibrium point. The convergence result is based on the Lojasiewicz gradient inequality; optimal convergence rates are also derived, as well as a stability result. We show how our results apply to a large variety of standard time discretizations of gradient-like flows. Schemes with variable time step are considered and optimal conditions on the maximal step size are derived. Applications to time and space discretizations of the Allen–Cahn equation, the sine–Gordon equation and a damped wave equation are given.

Description: This paper presents quadratic finite-volume methods for elliptic and parabolic problems on quadrilateral meshes that use Barlow points (optimal stress points) for dual partitions. Introducing Barlow points into the finite-volume formulations results in better approximation properties at the cost of loss of symmetry. The novel ‘symmetrization’ technique adopted in this paper allows us to derive optimal-order error estimates in the H 1 - and L 2 -norms for elliptic problems and in the L ( H 1 )- and L ( L 2 )-norms for parabolic problems. Superconvergence of the difference between the gradients of the finite-volume solution and the interpolant can also be derived. Numerical results confirm the proved error estimates.

Description: A linear parabolic differential equation on a moving surface is discretized in space by evolving-surface finite elements and in time by backward difference formulas (BDFs). Using results from Dahlquist's G-stability theory and Nevanlinna & Odeh's multiplier technique together with properties of the spatial semidiscretization, stability of the full discretization is proved for BDF methods up to order 5 and optimal-order convergence is shown. Numerical experiments illustrate the behaviour of the fully discrete method.

Description: In this article, we develop the a priori and a posteriori error analysis of hp -version interior penalty discontinuous Galerkin finite element methods for strongly monotone quasi-Newtonian fluid flows in a bounded Lipschitz domain R d , d = 2, 3. In the latter case, computable upper and lower bounds on the error are derived in terms of a natural energy norm, which are explicit in the local mesh size and local polynomial degree of the approximating finite element method. A series of numerical experiments illustrate the performance of the proposed a posteriori error indicators within an automatic hp -adaptive refinement algorithm.

Description: In recent years, it has become increasingly clear that the critical issue in gradient methods is the choice of the step length, whereas using gradient as the search direction may lead to very effective algorithms, whose surprising behaviour has only been partially explained, mostly in terms of the spectrum of the Hessian matrix. On the other hand, the convergence of the classical Cauchy steepest descent (SD) method has been analysed extensively and related to the spectral properties of the Hessian matrix, but the connection with the spectrum of the Hessian has not been exploited much to modify the method in order to improve its behaviour. In this work, we show how, for convex quadratic problems, moving from some theoretical properties of the SD method, second-order information provided by the step length can be exploited to dramatically improve the usually poor practical behaviour of this method. This allows us to achieve computational results comparable with those of the Barzilai and Borwein algorithm, with the further advantage of monotonic behaviour.

Description: Motivation: Residue–residue contacts across the transmembrane helices dictate the three-dimensional topology of alpha-helical membrane proteins. However, contact determination through experiments is difficult because most transmembrane proteins are hard to crystallize. Results: We present a novel method (MemBrain) to derive transmembrane inter-helix contacts from amino acid sequences by combining correlated mutations and multiple machine learning classifiers. Tested on 60 non-redundant polytopic proteins using a strict leave-one-out cross-validation protocol, MemBrain achieves an average accuracy of 62%, which is 12.5% higher than the current best method from the literature. When applied to 13 recently solved G protein-coupled receptors, the MemBrain contact predictions helped increase the TM-score of the I-TASSER models by 37% in the transmembrane region. The number of foldable cases (TM-score 〉0.5) increased by 100%, where all G protein-coupled receptor templates and homologous templates with sequence identity 〉30% were excluded. These results demonstrate significant progress in contact prediction and a potential for contact-driven structure modeling of transmembrane proteins. Availability: www.csbio.sjtu.edu.cn/bioinf/MemBrain/ Contact: hbshen@sjtu.edu.cn or zhng@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Identification of protein–ligand binding sites is critical to protein function annotation and drug discovery. However, there is no method that could generate optimal binding site prediction for different protein types. Combination of complementary predictions is probably the most reliable solution to the problem. Results: We develop two new methods, one based on binding-specific substructure comparison (TM-SITE) and another on sequence profile alignment (S-SITE), for complementary binding site predictions. The methods are tested on a set of 500 non-redundant proteins harboring 814 natural, drug-like and metal ion molecules. Starting from low-resolution protein structure predictions, the methods successfully recognize 〉51% of binding residues with average Matthews correlation coefficient (MCC) significantly higher (with P -value 〈10 –9 in student t -test) than other state-of-the-art methods, including COFACTOR, FINDSITE and ConCavity. When combining TM-SITE and S-SITE with other structure-based programs, a consensus approach (COACH) can increase MCC by 15% over the best individual predictions. COACH was examined in the recent community-wide COMEO experiment and consistently ranked as the best method in last 22 individual datasets with the Area Under the Curve score 22.5% higher than the second best method. These data demonstrate a new robust approach to protein–ligand binding site recognition, which is ready for genome-wide structure-based function annotations. Availability: http://zhanglab.ccmb.med.umich.edu/COACH/ Contact: zhng@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The nucleosome is the basic repeating unit of chromatin. It contains two copies each of the four core histones H2A, H2B, H3 and H4 and about 147 bp of DNA. The residues of the histone proteins are subject to numerous post-translational modifications, such as methylation or acetylation. Chromatin immunoprecipitiation followed by sequencing (ChIP-seq) is a technique that provides genome-wide occupancy data of these modified histone proteins, and it requires appropriate computational methods. Results: We present NucHunter, an algorithm that uses the data from ChIP-seq experiments directed against many histone modifications to infer positioned nucleosomes. NucHunter annotates each of these nucleosomes with the intensities of the histone modifications. We demonstrate that these annotations can be used to infer nucleosomal states with distinct correlations to underlying genomic features and chromatin-related processes, such as transcriptional start sites, enhancers, elongation by RNA polymerase II and chromatin-mediated repression. Thus, NucHunter is a versatile tool that can be used to predict positioned nucleosomes from a panel of histone modification ChIP-seq experiments and infer distinct histone modification patterns associated to different chromatin states. Availability: The software is available at http://epigen.molgen.mpg.de/nuchunter/ . Contact: chung@molgen.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: In biomedical research a growing number of platforms and technologies are used to measure diverse but related information, and the task of clustering a set of objects based on multiple sources of data arises in several applications. Most current approaches to multisource clustering either independently determine a separate clustering for each data source or determine a single ‘joint’ clustering for all data sources. There is a need for more flexible approaches that simultaneously model the dependence and the heterogeneity of the data sources. Results: We propose an integrative statistical model that permits a separate clustering of the objects for each data source. These separate clusterings adhere loosely to an overall consensus clustering, and hence they are not independent. We describe a computationally scalable Bayesian framework for simultaneous estimation of both the consensus clustering and the source-specific clusterings. We demonstrate that this flexible approach is more robust than joint clustering of all data sources, and is more powerful than clustering each data source independently. We present an application to subtype identification of breast cancer tumor samples using publicly available data from The Cancer Genome Atlas. Availability: R code with instructions and examples is available at http://people.duke.edu/%7Eel113/software.html . Contact: Eric.Lock@duke.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: More and more evidences have indicated that long–non-coding RNAs (lncRNAs) play critical roles in many important biological processes. Therefore, mutations and dysregulations of these lncRNAs would contribute to the development of various complex diseases. Developing powerful computational models for potential disease-related lncRNAs identification would benefit biomarker identification and drug discovery for human disease diagnosis, treatment, prognosis and prevention. Results : In this article, we proposed the assumption that similar diseases tend to be associated with functionally similar lncRNAs. Then, we further developed the method of Laplacian Regularized Least Squares for LncRNA–Disease Association (LRLSLDA) in the semisupervised learning framework. Although known disease–lncRNA associations in the database are rare, LRLSLDA still obtained an AUC of 0.7760 in the leave-one-out cross validation, significantly improving the performance of previous methods. We also illustrated the performance of LRLSLDA is not sensitive (even robust) to the parameters selection and it can obtain a reliable performance in all the test classes. Plenty of potential disease–lncRNA associations were publicly released and some of them have been confirmed by recent results in biological experiments. It is anticipated that LRLSLDA could be an effective and important biological tool for biomedical research. Availability: The code of LRLSLDA is freely available at http://asdcd.amss.ac.cn/Software/Details/2 . Contact: xingchen@amss.ac.cn or yangy@amt.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Genomic repositories are rapidly growing, as witnessed by the 1000 Genomes or the UK10K projects. Hence, compression of multiple genomes of the same species has become an active research area in the past years. The well-known large redundancy in human sequences is not easy to exploit because of huge memory requirements from traditional compression algorithms. Results: We show how to obtain several times higher compression ratio than of the best reported results, on two large genome collections (1092 human and 775 plant genomes). Our inputs are variant call format files restricted to their essential fields. More precisely, our novel Ziv-Lempel-style compression algorithm squeezes a single human genome to ~400 KB. The key to high compression is to look for similarities across the whole collection, not just against one reference sequence, what is typical for existing solutions. Availability: http://sun.aei.polsl.pl/tgc (also as Supplementary Material) under a free license. Supplementary data: Supplementary data are available at Bioinformatics online. Contact: sebastian.deorowicz@polsl.pl

Description: Motivation:  Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. Results:  We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Availability:  Toolbox ‘NearOED’ available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org). Contact:   busettoa@inf.ethz.ch Supplementary information:   Supplementary data are available at Bioinformatics online.

Description: : Small RNA deep sequencing is widely used to characterize non-coding RNAs (ncRNAs) differentially expressed between two conditions, e.g. healthy and diseased individuals and to reveal insights into molecular mechanisms underlying condition-specific phenotypic traits. The ncRNAome is composed of a multitude of RNAs, such as transfer RNA, small nucleolar RNA and microRNA (miRNA), to name few. Here we present omiRas, a Web server for the annotation, comparison and visualization of interaction networks of ncRNAs derived from next-generation sequencing experiments of two different conditions. The Web tool allows the user to submit raw sequencing data and results are presented as: (i) static annotation results including length distribution, mapping statistics, alignments and quantification tables for each library as well as lists of differentially expressed ncRNAs between conditions and (ii) an interactive network visualization of user-selected miRNAs and their target genes based on the combination of several miRNA–mRNA interaction databases. Availability and Implementation: The omiRas Web server is implemented in Python, PostgreSQL, R and can be accessed at: http://tools.genxpro.net/omiras/ . Contact: rotter@genxpro.de Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: : We present PARSEC (PAtteRn Search and Contextualization), a new open source platform for guided discovery, allowing localization and biological characterization of short genomic sites in entire eukaryotic genomes. PARSEC can search for a sequence or a degenerated pattern. The retrieved set of genomic sites can be characterized in terms of (i) conservation in model organisms, (ii) genomic context (proximity to genes) and (iii) function of neighboring genes. These modules allow the user to explore, visualize, filter and extract biological knowledge from a set of short genomic regions such as transcription factor binding sites. Availability: Web site implemented in Java, JavaScript and C++, with all major browsers supported. Freely available at lbgi.fr/parsec. Source code is freely available at sourceforge.net/projects/genomicparsec. Contact: odile.lecompte@unistra.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : At the rate that prokaryotic genomes can now be generated, comparative genomics studies require a flexible method for quickly and accurately predicting orthologs among the rapidly changing set of genomes available. SPOCS implements a graph-based ortholog prediction method to generate a simple tab-delimited table of orthologs and in addition, html files that provide a visualization of the predicted ortholog/paralog relationships to which gene/protein expression metadata may be overlaid. Availability and Implementation: A SPOCS web application is freely available at http://cbb.pnnl.gov/portal/tools/spocs.html . Source code for Linux systems is also freely available under an open source license at http://cbb.pnnl.gov/portal/software/spocs.html ; the Boost C++ libraries and BLAST are required. Contact: leeann.mccue@pnnl.gov

Description: : Automated image processing has allowed cell migration research to evolve to a high-throughput research field. As a consequence, there is now an unmet need for data management in this domain. The absence of a generic management system for the quantitative data generated in cell migration assays results in each dataset being treated in isolation, making data comparison across experiments difficult. Moreover, by integrating quality control and analysis capabilities into such a data management system, the common practice of having to manually transfer data across different downstream analysis tools will be markedly sped up and made more robust. In addition, access to a data management solution creates gateways for data standardization, meta-analysis and structured public data dissemination. We here present CellMissy, a cross-platform data management system for cell migration data with a focus on wound healing data. CellMissy simplifies and automates data management, storage and analysis from the initial experimental set-up to data exploration. Availability and implementation: CellMissy is a cross-platform open-source software developed in Java. Source code and cross-platform binaries are freely available under the Apache2 open source license at http://cellmissy.googlecode.com . Contact: lennart.martens@ugent.be Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: Motivation: With the expansion of high-throughput technologies, understanding different kinds of genome-level data is a common task. MicroRNA (miRNA) is increasingly profiled using high-throughput technologies (microarrays or next-generation sequencing). The downstream analysis of miRNA targets can be difficult. Although there are many databases and algorithms to predict miRNA targets, there are few tools to integrate miRNA–gene interaction data into high-throughput genomic analyses. Results: We present targetHub, a CouchDB database of miRNA–gene interactions. TargetHub provides a programmer-friendly interface to access miRNA targets. The Web site provides RESTful access to miRNA–gene interactions with an assortment of gene and miRNA identifiers. It can be a useful tool to integrate miRNA target interaction data directly into high-throughput bioinformatics analyses. Availability: TargetHub is available on the web at http://app1.bioinformatics.mdanderson.org/tarhub/_design/basic/index.html . Contact: coombes.3@osu.edu

Description: Magma dynamics and time scales during the VEI 5, 2000 bp eruption of El Misti volcano, southern Peru (EM2000BP) are investigated to address cyclic explosive activity at this hazardous volcano. The 1·4 km 3 of pumice falls and flows have abundant mingled pumice of high-K, calc-alkaline rhyolite and andesite composition. Phenocryst zoning and compositions reveal mutual exchange of plagioclase between the two magmas; amphibole in the rhyolite was derived from the andesite. Amphiboles in the andesite are predominantly unrimmed crystals whereas those in the rhyolite mostly exhibit reaction rims. Phase equilibria indicate that the andesite formed at ~900–950°C and 2–3 kbar pressure and was water-saturated with 5·1–6·0 wt % H 2 O, broadly similar to El Misti magmas overall. Amphibole, plagioclase, Ti-magnetite, and two pyroxenes were the crystallizing phases. A separate rhyolite magma existed higher in the crust at a temperature of 816 ± 30°C and ~5% H 2 O in which only plagioclase and Fe–Ti oxides were stable. The lack of cognate amphibole in the rhyolite despite H 2 O saturation requires that it staged above the stability limit of amphibole (〈100 MPa). Exchange reactions in amphibole (dominantly pargasitic) and trace element partitioning in plagioclase indicate that both andesite and rhyolite magmas were broadly constant in temperature and H 2 O content. These constraints suggest that the initially separate rhyolite and deeper andesite magmas interacted by an initial andesite recharge event that resulted in mingling and crystal exchange. A period of 50–60 days is required for amphibole introduced into the rhyolite to develop reaction rims owing to decompression. These rims are dominated by plagioclase, a consequence of the Al-rich nature of the amphibole. The lack of reaction rims on amphibole in the andesite implicates a second, more-forceful and voluminous eruption-triggering recharge event during which andesite rose rapidly from source to surface in ≤5 days at ascent rates of at least 0·023 m s –1 . Further decompression-driven crystallization is recorded in plagioclase rims and microlite growth that may have contributed to a rapid increase in viscosity leading to explosive eruption. This VEI 5 plinian eruption shares characteristics with other explosive events at El Misti on a time scale of 2000–4000 years, suggesting periodic recharge-driven explosive activity.

Description: We report structural evidence of ductile strain localization in mantle pyroxenite from the spinel to plagioclase websterite transition in the Ronda Peridotite (southern Spain). Mapping shows that, in this domain, small-scale shear zones occurring at the base of the lithospheric section are systematically located within thin pyroxenite layers, suggesting that the pyroxenite was locally weaker than the host peridotite. Strain localization is associated with a sudden decrease of grain size and increasing volume fractions of plagioclase and amphibole as a result of a spinel to plagioclase phase transformation reaction during decompression. This reaction also fostered hydrogen extraction (‘dehydroxylation’) from clinopyroxene producing effective fluid saturation that catalyzed the synkinematic net-transfer reaction. This reaction produced fine-grained olivine and plagioclase, allowing the onset of grain-size sensitive creep and further strain localization in these pyroxenite bands. The strain localization in the pyroxenites is thus explained by their more fertile composition, which allowed earlier onset of the phase transition reactions. Geothermobarometry undertaken on compositionally zoned constituent minerals suggests that this positive feedback between reactions and deformation is associated with cooling from at least 1000°C to 700°C and decompression from 1·0 to 0·5 GPa.

Description: Motivation: Human miRNAs have recently been found to have important roles in viral replication. Understanding the patterns and details of human miRNA interactions during virus–host interactions may help uncover novel antiviral therapies. Based on the abundance of knowledge available regarding protein–protein interactions (PPI), virus–host protein interactions, experimentally validated human miRNA-target pairs and transcriptional regulation of human miRNAs, it is possible to explore the complex regulatory network that exists between viral proteins and human miRNAs at the system level. Results: By integrating current data regarding the virus–human interactome and human miRNA-target pairs, the overlap between targets of viral proteins and human miRNAs was identified and found to represent topologically important proteins (e.g. hubs or bottlenecks) at the global center of the human PPI network. Viral proteins and human miRNAs were also found to significantly target human PPI pairs. Furthermore, an overlap analysis of virus targets and transcription factors (TFs) of human miRNAs revealed that viral proteins preferentially target human miRNA TFs, representing a new pattern of virus–host interactions. Potential feedback loops formed by viruses, human miRNAs and miRNA TFs were also identified, and these may be exploited by viruses resulting in greater virulence and more effective replication strategies. Contact: boxc@bmi.ac.cn or ni.ming@163.com or sqwang@bmi.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: In sequencing studies of common diseases and quantitative traits, power to test rare and low frequency variants individually is weak. To improve power, a common approach is to combine statistical evidence from several genetic variants in a region. Major challenges are how to do the combining and which statistical framework to use. General approaches for testing association between rare variants and quantitative traits include aggregating genotypes and trait values, referred to as ‘collapsing’, or using a score-based variance component test. However, little attention has been paid to alternative models tailored for protein truncating variants. Recent studies have highlighted the important role that protein truncating variants, commonly referred to as ‘loss of function’ variants, may have on disease susceptibility and quantitative levels of biomarkers. We propose a Bayesian modelling framework for the analysis of protein truncating variants and quantitative traits. Results: Our simulation results show that our models have an advantage over the commonly used methods. We apply our models to sequence and exome-array data and discover strong evidence of association between low plasma triglyceride levels and protein truncating variants at APOC3 (Apolipoprotein C3). Availability: Software is available from http://www.well.ox.ac.uk/~rivas/mamba Contact: donnelly@well.ox.ac.uk

Description: Motivation: Structural information of macromolecular complexes provides key insights into the way they carry out their biological functions. Achieving high-resolution structural details with electron microscopy requires the identification of a large number (up to hundreds of thousands) of single particles from electron micrographs, which is a laborious task if it has to be manually done and constitutes a hurdle towards high-throughput. Automatic particle selection in micrographs is far from being settled and new and more robust algorithms are required to reduce the number of false positives and false negatives. Results: In this article, we introduce an automatic particle picker that learns from the user the kind of particles he is interested in. Particle candidates are quickly and robustly classified as particles or non-particles. A number of new discriminative shape-related features as well as some statistical description of the image grey intensities are used to train two support vector machine classifiers. Experimental results demonstrate that the proposed method: (i) has a considerably low computational complexity and (ii) provides results better or comparable with previously reported methods at a fraction of their computing time. Availability: The algorithm is fully implemented in the open-source Xmipp package and downloadable from http://xmipp.cnb.csic.es . Contact: vabrishami@cnb.csic.es or coss@cnb.csic.es Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: : Recent major cancer genome sequencing studies have used whole-genome sequencing to detect various types of genomic variation. However, a number of these studies have continued to rely on SNP array information to provide additional results for copy number and loss-of-heterozygosity estimation and assessing tumour purity. OncoSNP-SEQ is a statistical model-based approach for inferring copy number profiles directly from high-coverage whole genome sequencing data that is able to account for unknown tumour purity and ploidy. Availability: MATLAB code is available at the following URL: https://sites.google.com/site/oncosnpseq/ . Contact : c.yau@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Multi-Image Genome (MIG) viewer is a web-based application for visualizing, querying and filtering many thousands of genome browser regions as well as for exporting the data in a variety of formats. This methodology has been used successfully to analyze ChIP-Seq data and RNA-Seq data and to detect somatic mutations in genome resequencing projects. Availability: MIG is available at https://mig.molbiol.ox.ac.uk/mig/ Contact: simon.mcgowan@imm.ox.ac.uk

Description: : Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA–protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses. Availability: ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf . Contact: alper.kucukural@umassmed.edu or ccenik@stanford.edu

Description: Motivation: Kinases of the eukaryotic protein kinase superfamily are key regulators of most aspects eukaryotic cellular behavior and have provided several drug targets including kinases dysregulated in cancers. The rapid increase in the number of genomic sequences has created an acute need to identify and classify members of this important class of enzymes efficiently and accurately. Results: Kinannote produces a draft kinome and comparative analyses for a predicted proteome using a single line command, and it is currently the only tool that automatically classifies protein kinases using the controlled vocabulary of Hanks and Hunter [Hanks and Hunter (1995)]. A hidden Markov model in combination with a position-specific scoring matrix is used by Kinannote to identify kinases, which are subsequently classified using a BLAST comparison with a local version of KinBase, the curated protein kinase dataset from www.kinase.com . Kinannote was tested on the predicted proteomes from four divergent species. The average sensitivity and precision for kinome retrieval from the test species are 94.4 and 96.8%. The ability of Kinannote to classify identified kinases was also evaluated, and the average sensitivity and precision for full classification of conserved kinases are 71.5 and 82.5%, respectively. Kinannote has had a significant impact on eukaryotic genome annotation, providing protein kinase annotations for 36 genomes made public by the Broad Institute in the period spanning 2009 to the present. Availability: Kinannote is freely available at http://sourceforge.net/projects/kinannote . Contact: jmgold@broadinstitute.org Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Quantification of lipids is a primary goal in lipidomics. In direct infusion/injection (or shotgun) lipidomics, accurate downstream identification and quantitation requires accurate summarization of repetitive peak measurements. Imprecise peak summarization multiplies downstream error by propagating into species identification and intensity estimation. To our knowledge, this is the first analysis of direct infusion peak summarization in the literature. Results: We present two novel peak summarization algorithms for direct infusion samples and compare them with an off-machine ad hoc summarization algorithm as well as with the propriety Xcalibur algorithm. Our statistical agglomeration algorithm reduces peakwise error by 38% mass/charge (m/z) and 44% (intensity) compared with the ad hoc method over three datasets. Pointwise error is reduced by 23% (m/z). Compared with Xcalibur, our statistical agglomeration algorithm produces 68% less m/z error and 51% less intensity error on average on two comparable datasets. Availability: The source code for Statistical Agglomeration and the datasets used are freely available for non-commercial purposes at https://github.com/optimusmoose/statistical_agglomeration . Modified Bin Aggolmeration is freely available in MSpire, an open source mass spectrometry package at https://github.com/princelab/mspire/ . Contact: 2robsmith@gmail.com or jtprince@chem.byu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Liquid chromatography coupled to mass spectrometry (LC-MS) is the dominant technological platform for proteomics. An LC-MS analysis of a complex biological sample can be visualized as a ‘map’ of which the positional coordinates are the mass-to-charge ratio (m/z) and chromatographic retention time (RT) of the chemical species profiled. Label-free quantitative proteomics requires the alignment and comparison of multiple LC-MS maps to ascertain the reproducibility of experiments or reveal proteome changes under different conditions. The main challenge in this task lies in correcting inevitable RT shifts. Similar, but not identical, LC instruments and settings can cause peptides to elute at very different times and sometimes in a different order, violating the assumptions of many state-of-the-art alignment tools. To meet this challenge, we developed LWBMatch, a new algorithm based on weighted bipartite matching. Unlike existing tools, which search for accurate warping functions to correct RT shifts, we directly seek a peak-to-peak mapping by maximizing a global similarity function between two LC-MS maps. For alignment tasks with large RT shifts (〉500 s), an approximate warping function is determined by locally weighted scatterplot smoothing of potential matched features, detected using a novel voting scheme based on co-elution. For validation, we defined the ground truth for alignment success based on tandem mass spectrometry identifications from sequence searching. We showed that our method outperforms several existing tools in terms of precision and recall, and is capable of aligning maps from different instruments and settings. Availability: Available at https://sourceforge.net/projects/rt-alignment/ . Contact: kehlam@ust.hk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : We propose SW#, a new CUDA graphical processor unit-enabled and memory-efficient implementation of dynamic programming algorithm, for local alignment. It can be used as either a stand-alone application or a library. Although there are other graphical processor unit implementations of the Smith–Waterman algorithm, SW# is the only one publicly available that can produce sequence alignments on genome-wide scale. For long sequences, it is at least a few hundred times faster than a CPU version of the same algorithm. Availability: Source code and installation instructions freely available for download at http://complex.zesoi.fer.hr/SW.html . Contact: mile.sikic@fer.hr Supplementary information: Supplementary results are available at Bioinformatics online.

Description: In recent years, there has been an enormous interest in developing methods for the approximation of manifold-valued functions. In this paper, we focus on the manifold of symmetric positive-definite (SPD) matrices. We investigate the use of SPD-matrix means to adapt linear positive approximation methods to SPD-matrix-valued functions. Specifically, we adapt corner-cutting subdivision schemes and Bernstein operators. We present the concept of admissible matrix means and study the adapted approximation schemes based on them. Two important cases of admissible matrix means are treated in detail: the exp–log and the geometric matrix means. We derive special properties of the approximation schemes based on these means. The geometric mean is found to be superior in the sense of preserving more properties of the data, such as monotonicity and convexity. Furthermore, we give error bounds for the approximation of univariate SPD-matrix-valued functions by the adapted operators.

Description: We present a mass-preserving scheme for the stochastic nonlinear Schrödinger equation with multiplicative noise of Stratonovich type. It is a splitting scheme and we present an explicit formula for solving the sub-step related to the nonlinear part. The scheme is unconditionally stable in the L 2 norm. For the linear stochastic Schrödinger equation, we prove that the scheme has a strong convergence rate in time equal to 1, which is not common for stochastic partial differential equations with noise depending on space and time.

Description: A numerical scheme for the approximation of the elastic flow of inextensible curves is devised and convergence of approximations to exact solutions of the nonlinear time-dependent partial differential equation is proved. The nonlinear, pointwise constraint of local length preservation is linearized about a previous solution in each time step which leads to a sequence of linear saddle-point problems. The spatial discretization is based on piecewise Bézier curves and the resulting semiimplicit scheme is unconditionally stable and convergent.

Description: We study the coercivity properties and the norm dependence on the wave-number k of certain regularized combined field boundary integral operators that we recently introduced for the solution of two- and three-dimensional acoustic scattering problems with Neumann boundary conditions. We show that in the case of circular and spherical boundaries, our regularized combined field boundary integral operators are L 2 coercive for large enough values of the coupling parameter, and that the norms of these operators are bounded by constant multiples of the coupling parameter. We establish that the norms of the regularized combined field boundary integral operators grow modestly with the wave-number k for smooth boundaries and we provide numerical evidence that these operators are L 2 coercive for two-dimensional starlike boundaries. We present and analyse a fully discrete collocation (Nyström) method for the solution of two-dimensional acoustic scattering problems with Neumann boundary conditions based on regularized combined field integral equations. In particular, for analytic boundaries and boundary data, we establish pointwise superalgebraic convergence rates of the discrete solutions.

Description: The classical theory of Gaussian quadrature assumes a positive weight function. We will show that in some cases Gaussian rules can be constructed with respect to an oscillatory weight, yielding methods with complex quadrature nodes and positive weights. These rules are well suited to highly oscillatory integrals because they attain optimal asymptotic order. We show that, for the Fourier oscillator, this approach yields the numerical method of steepest descent, a method with optimal asymptotic order that has previously been proposed for this class of integrals. However, the approach readily extends to more general kernels, such as Bessel functions that appear as the kernel of the Hankel transform.

Description: We consider anisotropic Allen–Cahn equations with interfacial energy induced by an anisotropic surface energy density . Assuming that is positive, positively homogeneous of degree 1, strictly convex in tangential directions to the unit sphere and sufficiently smooth, we show the stability of various time discretizations. In particular, we consider a fully implicit and a linearized time discretization of the interfacial energy combined with implicit and semiimplicit time discretizations of the double-well potential. In the semiimplicit variant, concave terms are taken explicitly. The arising discrete spatial problems are solved by globally convergent truncated nonsmooth Newton multigrid methods. Numerical experiments show the accuracy of the different discretizations. We also illustrate that pinch-off under anisotropic mean curvature flow is no longer invariant under rotation of the initial configuration for a fixed orientation of the anisotropy.

Description: : MicroRNAs (miRNAs) have been extensively studied owing to their important regulatory roles in genic expression. An increasingly number of reports are performing extensive data mining in small RNA sequencing libraries to detect miRNAs isoforms and also 5' and 3' post-transcriptional nucleotide additions, as well as edited miRNAs sequences. A ready to use pipeline, isomiRID, was developed to standardize and automatize the search for miRNAs isoforms in high-throughput small RNA sequencing libraries. Availability: isomiRID is a command line Python script available at http://www.ufrgs.br/RNAi/isomiRID/ . Contact: rogerio.margis@ufrgs.br Supplementary information: Supplementary Date are available at Bioinformatics online.

Description: Motivation: Understanding the details of protein–RNA interactions is important to reveal the functions of both the RNAs and the proteins. In these interactions, the secondary structures of the RNAs play an important role. Because RNA secondary structures in protein–RNA complexes are variable, considering the ensemble of RNA secondary structures is a useful approach. In particular, recent studies have supported the idea that, in the analysis of RNA secondary structures, the base-pairing probabilities (BPPs) of RNAs (i.e. the probabilities of forming a base pair in the ensemble of RNA secondary structures) provide richer and more robust information about the structures than a single RNA secondary structure, for example, the minimum free energy structure or a snapshot of structures in the Protein Data Bank. However, there has been no investigation of the BPPs in protein–RNA interactions. Results: In this study, we analyzed BPPs of RNA molecules involved in known protein–RNA complexes in the Protein Data Bank. Our analysis suggests that, in the tertiary structures, the BPPs (which are computed using only sequence information) for unpaired nucleotides with intermolecular hydrogen bonds (hbonds) to amino acids were significantly lower than those for unpaired nucleotides without hbonds. On the other hand, no difference was found between the BPPs for paired nucleotides with and without intermolecular hbonds. Those findings were commonly supported by three probabilistic models, which provide the ensemble of RNA secondary structures, including the McCaskill model based on Turner’s free energy of secondary structures. Contact: iwakiri@cb.k.u-tokyo.ac.jp or mhamada@cb.k.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Gene fusions resulting from chromosomal aberrations are an important cause of cancer. The complexity of genomic changes in certain cancer types has hampered the identification of gene fusions by molecular cytogenetic methods, especially in carcinomas. This is changing with the advent of next-generation sequencing, which is detecting a substantial number of new fusion transcripts in individual cancer genomes. However, this poses the challenge of identifying those fusions with greater oncogenic potential amid a background of ‘passenger’ fusion sequences. Results: In the present work, we have used some recently identified genomic hallmarks of oncogenic fusion genes to develop a pipeline for the classification of fusion sequences, namely, Oncofuse. The pipeline predicts the oncogenic potential of novel fusion genes, calculating the probability that a fusion sequence behaves as ‘driver’ of the oncogenic process based on features present in known oncogenic fusions. Cross-validation and extensive validation tests on independent datasets suggest a robust behavior with good precision and recall rates. We believe that Oncofuse could become a useful tool to guide experimental validation studies of novel fusion sequences found during next-generation sequencing analysis of cancer transcriptomes. Availability and implementation: Oncofuse is a naive Bayes Network Classifier trained and tested using Weka machine learning package. The pipeline is executed by running a Java/Groovy script, available for download at www.unav.es/genetica/oncofuse.html . Contact: fnovo@unav.es Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: High-throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts. However, the extensive dynamic range of gene expression, technical limitations and biases, as well as the observed complexity of the transcriptional landscape, pose profound computational challenges for transcriptome reconstruction. Results: We present the novel framework MITIE (Mixed Integer Transcript IdEntification) for simultaneous transcript reconstruction and quantification. We define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data and show how to find the optimal solution using Mixed Integer Programming. MITIE can (i) take advantage of known transcripts, (ii) reconstruct and quantify transcripts simultaneously in multiple samples, and (iii) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data. When compared with state-of-the-art approaches, MITIE proves to be significantly more sensitive and overall more accurate. Moreover, MITIE yields substantial performance gains when used with multiple samples. We applied our system to 38 Drosophila melanogaster modENCODE RNA-Seq libraries and estimated the sensitivity of reconstructing omitted transcript annotations and the specificity with respect to annotated transcripts. Our results corroborate that a well-motivated objective paired with appropriate optimization techniques lead to significant improvements over the state-of-the-art in transcriptome reconstruction. Availability: MITIE is implemented in C++ and is available from http://bioweb.me/mitie under the GPL license. Contact: Jonas_Behr@web.de and raetsch@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation : Due to rapid technological advances, a wide range of different measurements can be obtained from a given biological sample including single nucleotide polymorphisms, copy number variation, gene expression levels, DNA methylation and proteomic profiles. Each of these distinct measurements provides the means to characterize a certain aspect of biological diversity, and a fundamental problem of broad interest concerns the discovery of shared patterns of variation across different data types. Such data types are heterogeneous in the sense that they represent measurements taken at different scales or represented by different data structures. Results : We propose a distance-based statistical test, the generalized RV (GRV) test, to assess whether there is a common and non-random pattern of variability between paired biological measurements obtained from the same random sample. The measurements enter the test through the use of two distance measures, which can be chosen to capture a particular aspect of the data. An approximate null distribution is proposed to compute P -values in closed-form and without the need to perform costly Monte Carlo permutation procedures. Compared with the classical Mantel test for association between distance matrices, the GRV test has been found to be more powerful in a number of simulation settings. We also demonstrate how the GRV test can be used to detect biological pathways in which genetic variability is associated to variation in gene expression levels in an ovarian cancer sample, and present results obtained from two independent cohorts. Availability : R code to compute the GRV test is freely available from http://www2.imperial.ac.uk/~gmontana Contact : g.montana@imperial.ac.uk Supplementary data : Supplementary data are available at Bioinformatics online.

Description: Motivation: Alzheimer’s disease (AD) is a severe neurodegenerative disease of the central nervous system that may be caused by perturbation of regulatory pathways rather than the dysfunction of a single gene. However, the pathology of AD has yet to be fully elucidated. Results: In this study, we systematically analyzed AD-related mRNA and miRNA expression profiles as well as curated transcription factor (TF) and miRNA regulation to identify active TF and miRNA regulatory pathways in AD. By mapping differentially expressed genes and miRNAs to the curated TF and miRNA regulatory network as active seed nodes, we obtained a potential active subnetwork in AD. Next, by using the breadth-first-search technique, potential active regulatory pathways, which are the regulatory cascade of TFs, miRNAs and their target genes, were identified. Finally, based on the known AD-related genes and miRNAs, the hypergeometric test was used to identify active pathways in AD. As a result, nine pathways were found to be significantly activated in AD. A comprehensive literature review revealed that eight out of nine genes and miRNAs in these active pathways were associated with AD. In addition, we inferred that the pathway hsa-miR-146a-〉STAT1-〉MYC, which is the source of all nine significantly active pathways, may play an important role in AD progression, which should be further validated by biological experiments. Thus, this study provides an effective approach to finding active TF and miRNA regulatory pathways in AD and can be easily applied to other complex diseases. Contact: lixia@hrbmu.edu.cn or lw2247@gmail.com . Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: 3' end processing is important for transcription termination, mRNA stability and regulation of gene expression. To identify 3' ends, most techniques use an oligo-dT primer to construct deep sequencing libraries. However, this approach can lead to identification of artifactual polyadenylation sites due to internal priming in homopolymeric stretches of adenines. Although heuristic filters have been applied in these cases, they typically result in a high proportion of both false-positive and -negative classifications. Therefore, there is a need to develop improved algorithms to better identify mis-priming events in oligo-dT primed sequences. Results: By analyzing sequence features flanking 3' ends derived from oligo-dT-based sequencing, we developed a naïve Bayes classifier to classify them as true or false/internally primed. The resulting algorithm is highly accurate, outperforms previous heuristic filters and facilitates identification of novel polyadenylation sites. Contact: nathan.lawson@umassmed.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The lack of reliable, comprehensive gold standards complicates the development of many bioinformatics tools, particularly for the analysis of expression data and biological networks. Simulation approaches can provide provisional gold standards, such as regulatory networks, for the assessment of network inference methods. However, this just defers the problem, as it is difficult to assess how closely simulators emulate the properties of real data. Results: In analogy to Turing’s test discriminating humans and computers based on responses to questions, we systematically compare real and artificial systems based on their gene expression output. Different expression data analysis techniques such as clustering are applied to both types of datasets. We define and extract distributions of properties from the results, for instance, distributions of cluster quality measures or transcription factor activity patterns. Distributions of properties are represented as histograms to enable the comparison of artificial and real datasets. We examine three frequently used simulators that generate expression data from parameterized regulatory networks. We identify features distinguishing real from artificial datasets that suggest how simulators could be adapted to better emulate real datasets and, thus, become more suitable for the evaluation of data analysis tools. Availability: See http://www2.bio.ifi.lmu.de/~kueffner/attfad/ and the supplement for precomputed analyses; other compendia can be analyzed via the CRAN package attfad. The full datasets can be obtained from http://www2.bio.ifi.lmu.de/~kueffner/attfad/data.tar.gz . Contact: robert.kueffner@bio.ifi.lmu.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The two major epigenetic modifications of cytosines, 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC), coexist with each other in a range of mammalian cell populations. Increasing evidence points to important roles of 5-hmC in demethylation of 5-mC and epigenomic regulation in development. Recently developed experimental methods allow direct single-base profiling of either 5-hmC or 5-mC. Meaningful analyses seem to require combining these experiments with bisulfite sequencing, but doing so naively produces inconsistent estimates of 5-mC or 5-hmC levels. Results: We present a method to jointly model read counts from bisulfite sequencing, oxidative bisulfite sequencing and Tet-Assisted Bisulfite sequencing, providing simultaneous estimates of 5-hmC and 5-mC levels that are consistent across experiment types. Availability: http://smithlab.usc.edu/software/mlml Contact: andrewds@usc.edu Supplementary information: Supplementary material is available at Bioinformatics online.

Description: Motivation: A major goal in genomic research is to identify genes that may jointly influence a biological response. From many years of intensive biomedical research, a large body of biological knowledge, or pathway information, has accumulated in available databases. There is a strong interest in leveraging these pathways to improve the statistical power and interpretability in studying gene networks associated with complex phenotypes. This prior information is a valuable complement to large-scale genomic data such as gene expression data generated from microarrays. However, it is a non-trivial task to effectively integrate available biological knowledge into gene expression data when reconstructing gene networks. Results: In this article, we developed and applied a Lasso method from a Bayesian perspective, a method we call prior Lasso (pLasso), for the reconstruction of gene networks. In this method, we partition edges between genes into two subsets: one subset of edges is present in known pathways, whereas the other has no prior information associated. Our method assigns different prior distributions to each subset according to a modified Bayesian information criterion that incorporates prior knowledge on both the network structure and the pathway information. Simulation studies have indicated that the method is more effective in recovering the underlying network than a traditional Lasso method that does not use the prior information. We applied pLasso to microarray gene expression datasets, where we used information from the Pathway Commons (PC) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as prior information for the network reconstruction, and successfully identified network hub genes associated with clinical outcome in cancer patients. Availability: The source code is available at http://nba.uth.tmc.edu/homepage/liu/pLasso . Contact: Yin.Liu@uth.tmc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : One approach to infer functions of new proteins from their homologs utilizes visualization of an all-against-all pairwise similarity network (A2ApsN) that exploits the speed of BLAST and avoids the complexity of multiple sequence alignment. However, identifying functions of the protein clusters in A2ApsN is never trivial, due to a lack of linking characterized proteins to their relevant information in current software packages. Given the database errors introduced by automatic annotation transfer, functional deduction should be made from proteins with experimental studies, i.e. ‘reference proteins’. Here, we present a web server, termed Pclust, which provides a user-friendly interface to visualize the A2ApsN, placing emphasis on such ‘reference proteins’ and providing access to their full information in source databases, e.g. articles in PubMed. The identification of ‘reference proteins’ and the ease of cross-database linkage will facilitate understanding the functions of protein clusters in the network, thus promoting interpretation of proteins of interest. Availability: The Pclust server is freely available at http://prodata.swmed.edu/pclust Contact: grishin@chop.swmed.edu Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: : The understanding of the biological role of RNA molecules has changed. Although it is widely accepted that RNAs play important regulatory roles without necessarily coding for proteins, the functions of many of these non-coding RNAs are unknown. Thus, determining or modeling the 3D structure of RNA molecules as well as assessing their accuracy and stability has become of great importance for characterizing their functional activity. Here, we introduce a new web application, WebRASP, that uses knowledge-based potentials for scoring RNA structures based on distance-dependent pairwise atomic interactions. This web server allows the users to upload a structure in PDB format, select several options to visualize the structure and calculate the energy profile. The server contains online help, tutorials and links to other related resources. We believe this server will be a useful tool for predicting and assessing the quality of RNA 3D structures. Availability and implementation: The web server is available at http://melolab.org/webrasp . It has been tested on the most popular web browsers and requires Java plugin for Jmol visualization. Contact: fmelo@bio.puc.cl

Description: Contact: Wenhua.Wei@igmm.ed.ac.uk

Description: : Scaffold network generator (SNG) is an open-source command-line utility that computes the hierarchical network of scaffolds that define a large set of input molecules. Scaffold networks are useful for visualizing, analysing and understanding the chemical data that is increasingly available through large public repositories like PubChem. For example, some groups have used scaffold networks to identify missed-actives in high-throughput screens of small molecules with bioassays. Substantially improving on existing software, SNG is robust enough to work on millions of molecules at a time with a simple command-line interface. Availability and implementation: SNG is accessible at http://swami.wustl.edu/sng Contact: swamidass@wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : BioPAX is a community-developed standard language for biological pathway data. A key functionality required for efficient BioPAX data exchange is validation— detecting errors and inconsistencies in BioPAX documents. The BioPAX Validator is a command-line tool, Java library and online web service for BioPAX that performs 〉100 classes of consistency checks. Availability and implementation: The validator recognizes common syntactic errors and semantic inconsistencies and reports them in a customizable human readable format. It can also automatically fix some errors and normalize BioPAX data. Since its release, the validator has become a critical tool for the pathway informatics community, detecting thousands of errors and helping substantially increase the conformity and uniformity of BioPAX-formatted data. The BioPAX Validator is open source and released under LGPL v3 license. All sources, binaries and documentation can be found at sf.net/p/biopax, and the latest stable version of the web application is available at biopax.org/validator. Contact: igor.rodchenkov@utoronto.ca or gary.bader@utoronto.ca

Description: : Non-linear calibration is a widely used method for quantifying biomarkers wherein concentration-response curves estimated using samples of known concentrations are used to predict the biomarker concentrations in the samples of interest. The R package nCal fills an important gap in the open source, stand-alone software for performing non-linear calibration. For curve fitting, nCal provides a new implementation of a robust, Bayesian hierarchical five-parameter logistic model. nCal supports a simple graphical user interface that can be used by laboratory scientists, and contains functionality for importing data from the multiplex bead array assay instrumentation. Availability: The R package ‘nCal’ is available from http://cran.r-project.org/web/packages/nCal/ under GPL-2 or later. Contact: yfong@fhcrc.org Supplementary information: Supplementary information is available in the form of an R package vignette at the above repository and an FAQ at http://research.fhcrc.org/youyifong/en/resources/ncal.html .

Description: Motivation: Extensive DNA sequencing of tumor and matched normal samples using exome and whole-genome sequencing technologies has enabled the discovery of recurrent genetic alterations in cancer cells, but variability in stromal contamination and subclonal heterogeneity still present a severe challenge to available detection algorithms. Results: Here, we describe publicly available software, Shimmer, which accurately detects somatic single-nucleotide variants using statistical hypothesis testing with multiple testing correction. This program produces somatic single-nucleotide variant predictions with significantly higher sensitivity and accuracy than other available software when run on highly contaminated or heterogeneous samples, and it gives comparable sensitivity and accuracy when run on samples of high purity. Availability: http://www.github.com/nhansen/Shimmer Contact: nhansen@mail.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Mendel is one of the few statistical genetics packages that provide a full spectrum of gene mapping methods, ranging from parametric linkage in large pedigrees to genome-wide association with rare variants. Our latest additions to Mendel anticipate and respond to the needs of the genetics community. Compared with earlier versions, Mendel is faster and easier to use and has a wider range of applications. Supported platforms include Linux, MacOS and Windows. Availability : Free from www.genetics.ucla.edu/software/mendel Contact: klange@ucla.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: cis -regulatory DNA sequence elements, such as enhancers and silencers, function to control the spatial and temporal expression of their target genes. Although the overall levels of gene expression in large cell populations seem to be precisely controlled, transcription of individual genes in single cells is extremely variable in real time. It is, therefore, important to understand how these cis -regulatory elements function to dynamically control transcription at single-cell resolution. Recently, statistical methods have been proposed to back calculate the rates involved in mRNA transcription using parameter estimation of a mathematical model of transcription and translation. However, a major complication in these approaches is that some of the parameters, particularly those corresponding to the gene copy number and transcription rate, cannot be distinguished; therefore, these methods cannot be used when the copy number is unknown. Results: Here, we develop a hierarchical Bayesian model to estimate biokinetic parameters from live cell enhancer–promoter reporter measurements performed on a population of single cells. This allows us to investigate transcriptional dynamics when the copy number is variable across the population. We validate our method using synthetic data and then apply it to quantify the function of two known developmental enhancers in real time and in single cells. Availability: Supporting information is submitted with the article. Contact: d.j.woodcock@warwick.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The number of missense mutations being identified in cancer genomes has greatly increased as a consequence of technological advances and the reduced cost of whole-genome/whole-exome sequencing methods. However, a high proportion of the amino acid substitutions detected in cancer genomes have little or no effect on tumour progression (passenger mutations). Therefore, accurate automated methods capable of discriminating between driver (cancer-promoting) and passenger mutations are becoming increasingly important. In our previous work, we developed the Functional Analysis through Hidden Markov Models (FATHMM) software and, using a model weighted for inherited disease mutations, observed improved performances over alternative computational prediction algorithms. Here, we describe an adaptation of our original algorithm that incorporates a cancer-specific model to potentiate the functional analysis of driver mutations. Results: The performance of our algorithm was evaluated using two separate benchmarks. In our analysis, we observed improved performances when distinguishing between driver mutations and other germ line variants (both disease-causing and putatively neutral mutations). In addition, when discriminating between somatic driver and passenger mutations, we observed performances comparable with the leading computational prediction algorithms: SPF-Cancer and TransFIC. Availability and implementation: A web-based implementation of our cancer-specific model, including a downloadable stand-alone package, is available at http://fathmm.biocompute.org.uk . Contact: fathmm@biocompute.org.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Fragmented RNA immunoprecipitation combined with RNA sequencing enabled the unbiased study of RNA epigenome at a near single-base resolution; however, unique features of this new type of data call for novel computational techniques. Result: Through examining the connections of RNA epigenome sequencing data with two well-studied data types, ChIP-Seq and RNA-Seq, we unveiled the salient characteristics of this new data type. The computational strategies were discussed accordingly, and a novel data processing pipeline was proposed that combines several existing tools with a newly developed exome-based approach ‘exomePeak’ for detecting, representing and visualizing the post-transcriptional RNA modification sites on the transcriptome. Availability: The MATLAB package ‘exomePeak’ and additional details are available at http://compgenomics.utsa.edu/exomePeak/ . Contact: yufei.huang@utsa.edu or jmeng@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Contact: 2robsmith@gmail.com

Description: Motivation: Comparative studies are encouraged by the fast increase of data availability from the latest high-throughput techniques, in particular from functional genomic studies. Yet, the size of datasets, the challenge of complete orthologs findings and not last, the variety of identification formats, make information integration challenging. With HOMECAT, we aim to facilitate cross-species relationship identification and data mapping, by combining orthology predictions from several publicly available sources, a convenient interface for high-throughput data download and automatic identifier conversion into a Cytoscape plug-in, that provides both an integration with a large set of bioinformatics tools, as well as a user-friendly interface. Availability: HOMECAT and the Supplementary Materials are freely available at http://www.cbmc.it/homecat/ . Contact: simone.zorzan@univr.it Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : INstruct is a database of high-quality, 3D, structurally resolved protein interactome networks in human and six model organisms. INstruct combines the scale of available high-quality binary protein interaction data with the specificity of atomic-resolution structural information derived from co-crystal evidence using a tested interaction interface inference method. Its web interface is designed to allow for flexible search based on standard and organism-specific protein and gene-naming conventions, visualization of protein architecture highlighting interaction interfaces and viewing and downloading custom 3D structurally resolved interactome datasets. Availability: INstruct is freely available on the web at http://instruct.yulab.org with all major browsers supported. Contact: haiyuan.yu@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Targeted therapies interfering with specifically one protein activity are promising strategies in the treatment of diseases like cancer. However, accumulated empirical experience has shown that targeting multiple proteins in signaling networks involved in the disease is often necessary. Thus, one important problem in biomedical research is the design and prioritization of optimal combinations of interventions to repress a pathological behavior, while minimizing side-effects. OCSANA (optimal combinations of interventions from network analysis) is a new software designed to identify and prioritize optimal and minimal combinations of interventions to disrupt the paths between source nodes and target nodes. When specified by the user, OCSANA seeks to additionally minimize the side effects that a combination of interventions can cause on specified off-target nodes. With the crucial ability to cope with very large networks, OCSANA includes an exact solution and a novel selective enumeration approach for the combinatorial interventions’ problem. Availability: The latest version of OCSANA, implemented as a plugin for Cytoscape and distributed under LGPL license, is available together with source code at http://bioinfo.curie.fr/projects/ocsana . Supplementary information: Supplementary data are available at Bioinformatics online. Contact: paola.vera-licona@curie.fr

Description: : High-throughput microscopy data require a diversity of analytical approaches. However, the construction of workflows that use algorithms from different software packages is difficult owing to a lack of interoperability. To overcome this limitation, we present CellH5, an HDF5 data format for cell-based assays in high-throughput microscopy, which stores high-dimensional image data along with inter-object relations in graphs. CellH5Browser, an interactive gallery image browser, demonstrates the versatility and performance of the file format on live imaging data of dividing human cells. CellH5 provides new opportunities for integrated data analysis by multiple software platforms. Availability: Source code is freely available at www.github.com/cellh5 under the GPL license and at www.bioconductor.org/packages/release/bioc/html/rhdf5.html under the Artistic-2.0 license. Demo datasets and the CellH5Browser are available at www.cellh5.org . A Fiji importer for cellh5 will be released soon. Contact: daniel.gerlich@imba.oeaw.ac.at or christoph.sommer@imba.oeaw.ac.at Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Ribosome profiling is a new technique that allows monitoring locations of translating ribosomes on mRNA at a whole transcriptome level. A recent ribosome profiling study demonstrated that internal Shine–Dalgarno (SD) sequences have a major global effect on translation rates in bacteria: ribosomes pause at SD sites in mRNA. Therefore, it is important to understand how SD sites effect mRNA movement through the ribosome and generation of ribosome footprints. Results: Here, we provide evidence that in addition to pausing effect, internal SD sequences induce a caterpillar-like movement of mRNA through the ribosome cavity. Once an SD site binds to the ribosome, it remains attached to it while the ribosome decodes a few subsequent codons. This leads to asymmetric progressive elongation of ribosome footprints at the 3'-end. It is likely that internal SD sequences induce a pause not on a single, but on several adjacent codons. This finding is important for our understanding of mRNA movement through the ribosome and also should facilitate interpretation of ribosome profiling data. Contact: brave.oval.pan@gmail.com

Description: White spruce ( Picea glauca ) is a dominant conifer of the boreal forests of North America, and providing genomics resources for this commercially valuable tree will help improve forest management and conservation efforts. Sequencing and assembling the large and highly repetitive spruce genome though pushes the boundaries of the current technology. Here, we describe a whole-genome shotgun sequencing strategy using two Illumina sequencing platforms and an assembly approach using the ABySS software. We report a 20.8 giga base pairs draft genome in 4.9 million scaffolds, with a scaffold N50 of 20 356 bp. We demonstrate how recent improvements in the sequencing technology, especially increasing read lengths and paired end reads from longer fragments have a major impact on the assembly contiguity. We also note that scalable bioinformatics tools are instrumental in providing rapid draft assemblies. Availability: The Picea glauca genome sequencing and assembly data are available through NCBI (Accession#: ALWZ0100000000 PID: PRJNA83435). http://www.ncbi.nlm.nih.gov/bioproject/83435 . Contact: ibirol@bcgsc.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Abrupt reduction/resumption of thermal fluctuations of a force probe has been used to identify association/dissociation events of protein–ligand bonds. We show that off-rate of molecular dissociation can be estimated by the analysis of the bond lifetime, while the on-rate of molecular association can be estimated by the analysis of the waiting time between two neighboring bond events. However, the analysis relies heavily on subjective judgments and is time-consuming. To automate the process of mapping out bond events from thermal fluctuation data, we develop a hidden Markov model (HMM)-based method. Results: The HMM method represents the bond state by a hidden variable with two values: bound and unbound. The bond association/dissociation is visualized and pinpointed. We apply the method to analyze a key receptor–ligand interaction in the early stage of hemostasis and thrombosis: the von Willebrand factor (VWF) binding to platelet glycoprotein Ibα (GPIbα). The numbers of bond lifetime and waiting time events estimated by the HMM are much more than those estimated by a descriptive statistical method from the same set of raw data. The kinetic parameters estimated by the HMM are in excellent agreement with those by a descriptive statistical analysis, but have much smaller errors for both wild-type and two mutant VWF-A1 domains. Thus, the computerized analysis allows us to speed up the analysis and improve the quality of estimates of receptor–ligand binding kinetics. Contact: jeffwu@isye.gatech.edu or cheng.zhu@bme.gatech.edu

Description: Motivation: Approaches for testing sets of variants, such as a set of rare or common variants within a gene or pathway, for association with complex traits are important. In particular, set tests allow for aggregation of weak signal within a set, can capture interplay among variants and reduce the burden of multiple hypothesis testing. Until now, these approaches did not address confounding by family relatedness and population structure, a problem that is becoming more important as larger datasets are used to increase power. Results: We introduce a new approach for set tests that handles confounders. Our model is based on the linear mixed model and uses two random effects—one to capture the set association signal and one to capture confounders. We also introduce a computational speedup for two random-effects models that makes this approach feasible even for extremely large cohorts. Using this model with both the likelihood ratio test and score test, we find that the former yields more power while controlling type I error. Application of our approach to richly structured Genetic Analysis Workshop 14 data demonstrates that our method successfully corrects for population structure and family relatedness, whereas application of our method to a 15 000 individual Crohn’s disease case–control cohort demonstrates that it additionally recovers genes not recoverable by univariate analysis. Availability: A Python-based library implementing our approach is available at http://mscompbio.codeplex.com . Contact: jennl@microsoft.com or lippert@microsoft.com or heckerma@microsoft.com Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: It has been known for more than 2 decades that after RNA polymerase II (RNAPII) initiates transcription, it can enter into a paused or stalled state immediately downstream of the transcription start site before productive elongation. Recent advances in high-throughput genomic technologies facilitated the discovery that RNAPII pausing at promoters is a widespread physiologically regulated phenomenon. The molecular underpinnings of pausing are incompletely understood. The CCCTC-factor (CTCF) is a ubiquitous nuclear factor that has diverse regulatory functions, including a recently discovered role in promoting RNAPII pausing at splice sites. Results: In this study, we analyzed CTCF binding sites and nascent transcriptomic data from three different cell types, and found that promoter-proximal CTCF binding is significantly associated with RNAPII pausing. Contact: praveen_sethupathy@med.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: An important topic in systems biology is the reverse engineering of regulatory mechanisms through reconstruction of context-dependent gene networks. A major challenge is to identify the genes and the regulations specific to a condition or phenotype, given that regulatory processes are highly connected such that a specific response is typically accompanied by numerous collateral effects. In this study, we design a multi-layer approach that is able to reconstruct condition-specific genes and their regulation through an integrative analysis of large-scale information of gene expression, protein interaction and transcriptional regulation (transcription factor-target gene relationships). We establish the accuracy of our methodology against synthetic datasets, as well as a yeast dataset. We then extend the framework to the application of higher eukaryotic systems, including human breast cancer and Arabidopsis thaliana cold acclimation. Our study identified TACSTD2 (TROP2) as a target gene for human breast cancer and discovered its regulation by transcription factors CREB, as well as NFkB. We also predict KIF2C is a target gene for ER–/HER2– breast cancer and is positively regulated by E2F1. The predictions were further confirmed through experimental studies. Availability: The implementation and detailed protocol of the layer approach is available at http://www.egr.msu.edu/changroup/Protocols/Three-layer%20approach%20to%20reconstruct%20condition.html . Contact: krischan@egr.msu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Deciphering the modus operandi of dysregulated cellular mechanisms in cancer is critical to implicate novel cancer genes and develop effective anti-cancer therapies. Fundamental to this is meticulous tracking of the behavior of core modules, including complexes and pathways across specific conditions in cancer. Results: Here, we performed a straightforward yet systematic identification and comparison of modules across pancreatic normal and cancer tissue conditions by integrating PPI, gene-expression and mutation data. Our analysis revealed interesting change-patterns in gene composition and expression correlation particularly affecting modules responsible for genome stability. Although in most cases these changes indicated impairment of essential functions (e.g. of DNA damage repair), in several other cases we noticed strengthening of modules possibly abetting cancer. Some of these compensatory modules showed switches in transcription regulation and recruitment of tumor inducers (e.g. SOX2 through overexpression). In-depth analysis revealed novel genes in pancreatic cancer, which showed susceptibility to copy-number alterations (e.g. for USP15 in 17 of 67 cases), supported by literature evidence for their involvement in other tumors (e.g. USP15 in glioblastoma). Two of the identified genes, YWHAE and DISC1, further supported the nexus between neural genes and pancreatic carcinogenesis. Extension of this assessment to BRCA1 and BRCA2 breast tumors showed specific differences even across the two sub-types and revealed novel genes involved therein (e.g. TRIM5 and NCOA6). Availability: Our software CONTOURv1 is available at: http://bioinformatics.org.au/tools-data/ . Contact: m.ragan@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: As RNA interference is becoming a standard method for targeted gene perturbation, computational approaches to reverse engineer parts of biological networks based on measurable effects of RNAi become increasingly relevant. The vast majority of these methods use gene expression data, but little attention has been paid so far to other data types. Results : Here we present a method, which can infer gene networks from high-dimensional phenotypic perturbation effects on single cells recorded by time-lapse microscopy. We use data from the Mitocheck project to extract multiple shape, intensity and texture features at each frame. Features from different cells and movies are then aligned along the cell cycle time. Subsequently we use Dynamic Nested Effects Models (dynoNEMs) to estimate parts of the network structure between perturbed genes via a Markov Chain Monte Carlo approach. Our simulation results indicate a high reconstruction quality of this method. A reconstruction based on 22 gene knock downs yielded a network, where all edges could be explained via the biological literature. Availability : The implementation of dynoNEMs is part of the Bioconductor R-package nem . Contact: frohlich@bit.uni-bonn.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : UPDtool is a computational tool for detection and classification of uniparental disomy (UPD) in trio SNP-microarray experiments. UPDs are rare events of chromosomal malsegregation and describe the condition of two homologous chromosomes or homologous chromosomal segments that were inherited from one parent. The occurrence of UPD can be of major clinical relevance. Though high-throughput molecular screening techniques are widely used, detection of UPDs and especially the subclassification remains complex. We developed UPDtool to detect and classify UPDs from SNP microarray data of parent–child trios. The algorithm was tested using five positive controls including both iso- and heterodisomic segmental UPDs and 30 trios from the HapMap project as negative controls. With UPDtool, we were able to correctly identify all occurrences of non-mosaic UPD within our positive controls, whereas no occurrence of UPD was found within our negative controls. In addition, the chromosomal breakage points could be determined more precisely than by microsatellite analysis. Our results were compared with both the gold standard, microsatellite analysis and SNPtrio, another program available for UPD detection. UPDtool is platform independent, light weight and flexible. Because of its simple input format, UPDtool may also be used with other high-throughput technologies (e.g. next-generation sequencing). Availability and implementation: UPDtool executables, documentation and examples can be downloaded from http://www.uni-tuebingen.de/uni/thk/de/f-genomik-software.html . Contact: christopher.schroeder@med.uni-tuebingen.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: In this paper, we define a new finite element method for numerically approximating the solution of a partial differential equation in a bulk region coupled with a surface partial differential equation posed on the boundary of the bulk domain. The key idea is to take a polyhedral approximation of the bulk region consisting of a union of simplices, and to use piecewise polynomial boundary faces as an approximation of the surface. Two finite element spaces are defined, one in the bulk region and one on the surface, by taking the set of all continuous functions which are also piecewise polynomial on each bulk simplex or boundary face. We study this method in the context of a model elliptic problem; in particular, we look at well-posedness of the system using a variational formulation, derive perturbation estimates arising from domain approximation and apply these to find the optimal-order error estimates. A numerical experiment is described which demonstrates the order of convergence.

Description: As a model of more general contour integration problems we consider the numerical calculation of high-order derivatives of holomorphic functions using Cauchy's integral formula. Bornemann (2011, Accuracy and stability of computing high-order derivatives of analytic functions by Cauchy integrals. Found. Comput. Math. , 11 , 1–63) showed that the condition number of the Cauchy integral strongly depends on the chosen contour and solved the problem of minimizing the condition number for circular contours. In this paper, we minimize the condition number within the class of grid paths of step size h using Provan's algorithm for finding a shortest enclosing walk in weighted graphs embedded in the plane. Numerical examples show that optimal grid paths yield small condition numbers even in those cases where circular contours are known to be of limited use, such as for functions with branch-cut singularities.

Description: Anisotropic meshes are important for efficiently resolving incompressible flow problems that include boundary layer or corner singularity phenomena. Unfortunately, the stability of standard inf–sup stable mixed approximation methods is prone to degeneracy whenever the mesh aspect ratio becomes large. As an alternative, a stabilized mixed approximation method is considered here. Specifically, a robust a priori error estimate for the local jump stabilized Q 1 – P 0 approximation introduced by Kechkar & Silvester (1992, Analysis of locally stabilized mixed finite element methods for the Stokes problem. Math. Comp. , 58 , 1–10) is established for anisotropic meshes. Our numerical results demonstrate that the stabilized Q 1 – P 0 method is competitive with the nonconforming, nonparametric, rotated approximation method introduced by Rannacher & Turek (1992, Simple nonconforming quadrilateral Stokes element. Numer. Meth. Partial Differential Equations , 8 , 97–111).

Description: This work is about the numerical solution of the time-domain Maxwell's equations in dispersive propagation media by a discontinuous Galerkin time-domain method. The Debye model is used to describe the dispersive behaviour of the media. The resulting system of differential equations is solved using a centred-flux discontinuous Galerkin formulation for the discretization in space and a second-order leapfrog scheme for the integration in time. The numerical treatment of the dispersive model relies on an auxiliary differential equation approach similar to that which is adopted in the finite difference time-domain method. Stability estimates are derived through energy considerations and convergence is proved for both the semidiscrete and the fully discrete schemes.

Description: The parabolic singularly perturbed problem u xx ( x , t ) – x α u t ( x , t ) = f ( x , t ) is considered on the rectangular domain = (0,1) x (0, T ] with Dirichlet initial and boundary conditions. Here, is a small positive parameter and α is a positive constant. This problem is degenerate since the coefficient x α of u t vanishes along the side x = 0 of . Bounds on the derivatives of u are used to design a nonuniform mesh and a finite difference method on this mesh is constructed to solve the problem numerically. As the solution u is not in general uniformly bounded with respect to in the maximum norm, the convergence analysis of the numerical method requires the use of some unusual barrier functions and a special weighted discrete norm. Numerical examples are provided to support the theoretical results.

Description: We consider the numerical approximation of a general second-order semilinear parabolic stochastic partial differential equation driven by multiplicative and additive space–time noise. We examine convergence of exponential integrators for multiplicative and additive noise. We consider noise that is in a trace class and give a convergence proof in the root-mean-square L 2 norm. We discretize in space with the finite element method and in our implementation we examine both the finite element and the finite volume methods. We present results for a linear reaction–diffusion equation in two dimensions as well as a nonlinear example of a two-dimensional stochastic advection–diffusion–reaction equation motivated from realistic porous media flow.

Description: Sparse grids (Zenger, C. (1990) Sparse grids. Parallel Algorithms for Partial Differential Equations (W. Hackbusch ed.) Notes on Numerical Fluid Dynamics 31. Proceedings of the Sixth GAMM-Seminar; Bungartz, H.-J. & Griebel, M. (2004) Sparse grids. Acta Numer. , 13 , 1–123.) are tailored to the approximation of smooth high-dimensional functions. On a d -dimensional tensor product space, the number of grid points is N = O( h –1 |log h | d –1 ), where h is a mesh parameter. The so-called combination technique, based on hierarchical decomposition and extrapolation, requires specific multivariate error expansions of the discretization error on Cartesian grids to hold. We derive such error expansions for linear difference schemes through an error correction technique of semi-discretizations. We obtain overall error formulae of the type = O ( h p |log h | d –1 ) and analyse the convergence, with its dependence on dimension and smoothness, by examples of linear elliptic and parabolic problems, with numerical illustrations in up to eight dimensions.

Description: The numerical simulation of two-phase flow in a porous medium may lead, when using coupled finite volume schemes on structured grids, to the appearance of the so-called Grid Orientation Effect (GOE). We propose in this paper a procedure to eliminate this phenomenon, based on the use of new fluxes with a new stencil in the discrete version of the convection equation, without changing the discrete scheme for computing the pressure field. Numerical results show that the GOE does not significantly decrease with the size of the discretization using the initial scheme on the coupled problem, but that it is efficiently suppressed by the new procedure, even on coarse meshes. A mathematical study, based on a weak BV inequality using the new fluxes, confirms the convergence of the modified scheme in a particular case.

Description: The late Miocene and younger mafic back-arc lavas in the southern Puna of the central Andean plateau have been attributed to the aftermath of crustal and mantle lithospheric delamination or foundering. In this paper, we analyze in more detail the nature of the back-arc mafic suite magmas, including the conditions of magma generation in the mantle and of magma evolution during ascent and ponding in the crust, using extensive compositional data for phenocryst minerals and olivine-hosted melt inclusions in combination with published and new whole-rock chemical and isotopic data. We estimate that the primary melts last equilibrated with an enriched mantle source at temperatures near 1375°C and pressures near 2 GPa, which is near the base of the seismically determined ~60 km thick crust. A mantle source geochemically enriched by continental material introduced through delamination and subducted erosion processes is required to explain the coincidence of the high 87 Sr/ 86 Sr ratios (〉0·705) and high Sr concentrations (〉700 ppm) of the most primitive lavas (e.g. 9–10 wt % MgO, olivine Fo 88 ). The crystallization conditions inferred from mineral–melt equilibria indicate that olivine ( T = 1320–1220°C) was followed by clinopyroxene ( T = 1230–1140°C). Clinopyroxene–melt equilibration pressures of 0·7 to near 1 GPa in the most mafic samples indicate that the magmas crystallized at mid-crustal depths of 20–35 km, within a region of inferred partial melt accumulation based on the presence of low seismic velocity zones. Olivine-hosted melt inclusions indicate relatively dry melts (maximum 0·5 wt % H 2 O) with unusual high-Al basaltic compositions, which are attributed to the high-pressure suppression of plagioclase crystallization. A first stage of crustal contamination before mid-crustal accumulation and crystallization of the mafic magmas is suggested by high O-isotope ratios in olivine phenocrysts and negative Eu anomalies in clinopyroxene from the plagioclase-free mafic lavas. Mixing models based on trace elements and radiogenic isotopes suggest assimilation of silicic melt in the lower crust, similar to contemporaneous glassy dacites with steep REE patterns and negative Eu anomalies. A second stage of crustal assimilation at shallower depths is indicated by the mismatch of incompatible elements in clinopyroxene relative to bulk-rock compositions, by strong positive correlations of radiogenic isotopes with wt % SiO 2 , and by petrographic observation of partly resorbed and reacted quartz xenocrysts. Mixing calculations require the erupted magmas to have assimilated in total some 15–25% crust.

Description: Hornblende-bearing basanites and alkali basalts from the Rhön area of Germany (part of the Central European Volcanic Province; CEVP) have high TiO 2 (3–4 wt %), moderately high Mg# (mostly 〉0·50), variable Cr (400–30 ppm) and Ni (160–20 ppm) abundances, and are enriched in incompatible trace elements and rare earth elements (REE). In primitive mantle-normalized multi-element diagrams they show a strong depletion in Ba, Rb, and K relative to trace elements of similar incompatibility. Some alkali basalts and more differentiated rocks have lower Mg# and lower abundances of Ni and Cr, and have undergone fractionation of olivine, clinopyroxene, Fe–Ti oxides and amphibole. The trace element constraints (e.g. low Nb/U and Ce/Pb and the Nd–Sr–Pb isotope compositions of some basalts) indicate that assimilation of lower crustal material has modified the composition of the primary mantle-derived magmas. Most of the basanites and alkali basalts approach the Sr–Nd–Pb isotope compositions inferred for the EAR (European Asthenospheric Reservoir) component. Variations in REE abundances and correlations between REE ratios suggest partial melting of amphibole-bearing spinel peridotite containing a significant portion of non-peridotitic material (i.e. pyroxenite). The presence of residual amphibole, indicated by depletion of K and Rb relative to Ba and Nb, requires melting close to the asthenosphere–lithosphere boundary or within the lithospheric mantle, most probably of a veined mantle source. Temperature and pressure estimates indicate a depth of melting for the most primitive lavas at ~80 km at temperatures of ~1290°C. Based on Sr–Nd isotope and trace element constraints it is proposed that asthenospheric melts similar in composition to EAR melts observed elsewhere in the CEVP froze at the asthenosphere–lithosphere thermal boundary as veins in the lithospheric mantle. These veins were remelted after only short storage times by ascending asthenospheric melts, imposing the prominent amphibole signature upon the basalts. The fairly radiogenic Pb isotope signatures are expected to originate from melting of enriched, low melting temperature components incorporated in the depleted upper (asthenospheric) mantle and therefore do not require upwelling of deep-seated mantle sources for the Rhön or many other continental alkaline lavas with similar Pb isotope signatures.

Description: Motivation: Hidden Markov model, based on Li and Stephens model that takes into account chromosome sharing of multiple individuals, results in mainstream haplotype phasing algorithms for genotyping arrays and next-generation sequencing (NGS) data. However, existing methods based on this model assume that the allele count data are independently observed at individual sites and do not consider haplotype informative reads, i.e. reads that cover multiple heterozygous sites, which carry useful haplotype information. In our previous work, we developed a new hidden Markov model to incorporate a two-site joint emission term that captures the haplotype information across two adjacent sites. Although our model improves the accuracy of genotype calling and haplotype phasing, haplotype information in reads covering non-adjacent sites and/or more than two adjacent sites is not used because of the severe computational burden. Results: We develop a new probabilistic model for genotype calling and haplotype phasing from NGS data that incorporates haplotype information of multiple adjacent and/or non-adjacent sites covered by a read over an arbitrary distance. We develop a new hybrid Markov Chain Monte Carlo algorithm that combines the Gibbs sampling algorithm of HapSeq and Metropolis–Hastings algorithm and is computationally feasible. We show by simulation and real data from the 1000 Genomes Project that our model offers superior performance for haplotype phasing and genotype calling for population NGS data over existing methods. Availability: HapSeq2 is available at www.ssg.uab.edu/hapseq/ . Contact: dzhi@uab.edu or kzhang@uab.edu Supplementary information: Supplementary data are available at Bioinformatics online.