ALBERT

Description: The detailed, atomistic-level understanding of molecular signaling along the tumor-suppressive Hippo signaling pathway that controls tissue homeostasis by balancing cell proliferation and death through apoptosis is a promising avenue for the discovery of novel anticancer drug targets. The activation of kinases such as Mammalian STE20-Like Protein Kinases 1 and 2 (MST1 and MST2)—modulated through both homo- and heterodimerization (e.g. interactions with Ras association domain family, RASSF, enzymes)—is a key upstream event in this pathway and remains poorly understood. On the other hand, RASSFs (such as RASSF1A or RASSF5) act as important apoptosis activators and tumor suppressors, although their exact regulatory roles are also unclear. We present recent molecular studies of signaling along the Ras-RASSF-MST pathway, which controls growth and apoptosis in eukaryotic cells, including a variety of modern molecular modeling and simulation techniques. Using recently available structural information, we discuss the complex regulatory scenario according to which RASSFs perform dual signaling functions, either preventing or promoting MST2 activation, and thus control cell apoptosis. Here, we focus on recent studies highlighting the special role being played by the specific interactions between the helical Salvador/RASSF/Hippo (SARAH) domains of MST2 and RASSF1a or RASSF5 enzymes. These studies are crucial for integrating atomistic-level mechanistic information about the structures and conformational dynamics of interacting proteins, with information available on their system-level functions in cellular signaling.

Description: Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically ‘small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as ‘large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression data from a malaria vaccine trial by big-data-based edge biomarkers from module network rewiring-analysis. The illustrative results show that the identified module biomarkers can accurately distinguish vaccines with or without protection and outperformed previous reported gene signatures in terms of effectiveness and efficiency.

Description: Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods.

Description: One of the major challenges in biology concerns the integration of data across length and time scales into a consistent framework: how do macroscopic properties and functionalities arise from the molecular regulatory networks—and how can they change as a result of mutations? Morphogenesis provides an excellent model system to study how simple molecular networks robustly control complex processes on the macroscopic scale despite molecular noise, and how important functional variants can emerge from small genetic changes. Recent advancements in three-dimensional imaging technologies, computer algorithms and computer power now allow us to develop and analyse increasingly realistic models of biological control. Here, we present our pipeline for image-based modelling that includes the segmentation of images, the determination of displacement fields and the solution of systems of partial differential equations on the growing, embryonic domains. The development of suitable mathematical models, the data-based inference of parameter sets and the evaluation of competing models are still challenging, and current approaches are discussed.

Description: Owing greatly to the advancement of next-generation sequencing (NGS), the amount of NGS data is increasing rapidly. Although there are many NGS applications, one of the most commonly used techniques ‘RNA sequencing (RNA-seq)’ is rapidly replacing microarray-based techniques in laboratories around the world. As more and more of such techniques are standardized, allowing technicians to perform these experiments with minimal hands-on time and reduced experimental/operator-dependent biases, the bottleneck of such techniques is clearly visible; that is, data analysis. Further complicating the matter, increasing evidence suggests most of the genome is transcribed into RNA; however, the majority of these RNAs are not translated into proteins. These RNAs that do not become proteins are called ‘noncoding RNAs (ncRNAs)’. Although some time has passed since the discovery of ncRNAs, their annotations remain poor, making analysis of RNA-seq data challenging. Here, we examine the current limitations of RNA-seq analysis using case studies focused on the detection of novel transcripts and examination of their characteristics. Finally, we validate the presence of novel transcripts using biological experiments, showing novel transcripts can be accurately identified when a series of filters is applied. In conclusion, novel transcripts that are identified from RNA-seq must be examined carefully before proceeding to biological experiments.

Description: Functional genomics has enormous potential to facilitate our understanding of normal and disease-specific physiology. In the past decade, intensive research efforts have been focused on modeling functional relationship networks, which summarize the probability of gene co-functionality relationships. Such modeling can be based on either expression data only or heterogeneous data integration. Numerous methods have been deployed to infer the functional relationship networks, while most of them target the global (non-context-specific) functional relationship networks. However, it is expected that functional relationships consistently reprogram under different tissues or biological processes. Thus, advanced methods have been developed targeting tissue-specific or developmental stage-specific networks. This article brings together the state-of-the-art functional relationship network modeling methods, emphasizes the need for heterogeneous genomic data integration and context-specific network modeling and outlines future directions for functional relationship networks.

Description: Identification of drug–target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug–target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug–target associations on a large scale. In this review, databases and web servers involved in drug–target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug–target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug–target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug–target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data.

Description: Atherosclerosis is one of the principle pathologies of cardiovascular disease with blood cholesterol a significant risk factor. The World Health Organization estimates that approximately 2.5 million deaths occur annually because of the risk from elevated cholesterol, with 39% of adults worldwide at future risk. Atherosclerosis emerges from the combination of many dynamical factors, including haemodynamics, endothelial damage, innate immunity and sterol biochemistry. Despite its significance to public health, the dynamics that drive atherosclerosis remain poorly understood. As a disease that depends on multiple factors operating on different length scales, the natural framework to apply to atherosclerosis is mathematical and computational modelling. A computational model provides an integrated description of the disease and serves as an in silico experimental system from which we can learn about the disease and develop therapeutic hypotheses. Although the work completed in this area to date has been limited, there are clear signs that interest is growing and that a nascent field is establishing itself. This article discusses the current state of modelling in this area, bringing together many recent results for the first time. We review the work that has been done, discuss its scope and highlight the gaps in our understanding that could yield future opportunities.

Description: We present Bioinformatics Autodiscovery of Training Materials (BATMat), an open-source, Google-based, targeted, automatic search tool for training materials related to bioinformatics. BATMat helps gain access with one click to filtered and portable information containing links to existing materials (when present). It also offers functionality to sort results according to source site or title. Availability: http://imbatmat.com Contact: piar301@gmail.com

Description: In this article, I offer an interpretation of cycles in Dung-style argumentation frameworks in which even length cycles are treated as dilemmas and odd length cycles as paradoxes. The different properties of cycles with different parities arising from the use of preferred semantics are argued to be coherent with this interpretation.

Description: In abstract argumentation theory, preferred semantics has become one of the most popular approaches for determining the sets of arguments that can collectively be accepted. However, the description of preferred semantics, as it was originally stated by Dung, has a mainly technical and mathematical nature, making it difficult for lay persons to understand what the concept of preferred semantics is essentially about. In the current article, we aim to bridge the gap between mathematics and philosophy by providing a reformulation of (credulous) preferred semantics in terms of Socratic discussion. In order to do so, we first provide a (semi-)formal treatment of some of the concepts in Socratic dialogue.

Description: Recently, stage and cf 2 semantics for abstract argumentation attracted specific attention. By distancing from the notion of defence, they are capable to select arguments out of odd-length cycles. In case of cf 2 semantics, the SCC-recursive schema guarantees that important evaluation criteria for argumentation semantics, like directionality, weak- and $$\mathcal{C}$$ $$\mathcal{F}$$ -reinstatement, are fulfilled. Beside several desirable properties, both stage and cf 2 semantics still have some drawbacks. The stage semantics does not satisfy the above mentioned evaluation criteria, whereas cf 2 semantics produces some questionable results on frameworks with cycles of length ≥ 6. Therefore, we suggest to combine stage semantics with the SCC-recursive schema of cf 2 semantics. The resulting stage 2 semantics overcomes the problems regarding cf 2 and stage semantics. We study properties of stage 2 semantics and its relations to existing semantics, show that it fulfills the mentioned evaluation criteria, study strong equivalence for stage 2 semantics and provide a comprehensive complexity analysis of the associated reasoning problems. Besides the analysis of stage 2 semantics, we also complement existing complexity results for cf 2 by an analysis of tractable fragments and fixed parameter tractability. Furthermore, we provide answer-set programming (ASP) encodings for stage 2 semantics and labelling-based algorithms for cf 2 and stage 2 semantics.

Description: In this article, we propose a recursive semantics for warranted formulas in a general defeasible logic argumentation framework by formalizing a notion of collective (non-binary) conflict among arguments. The recursive semantics for warranted formulas is based on the intuitive grounds that if an argument is rejected, then further arguments built on top of it should also be rejected. The main characteristic of our recursive semantics is that an output (or extension) of a knowledge base is a pair consisting of a set of warranted and a set of blocked formulas. Arguments for both warranted and blocked formulas are recursively based on warranted formulas but, while warranted formulas do not generate any collective conflict, blocked conclusions do. Formulas that are neither warranted nor blocked correspond to rejected formulas. Then we extend the framework by attaching levels of preference to defeasible knowledge items and by providing a level-wise definition of warranted and blocked formulas. After we consider the warrant recursive semantics for the particular framework of Possibilistic Defeasible Logic Programming (RP-DeLP for short). Since RP-DeLP programmes may have multiple outputs, we define the maximal ideal output of an RP-DeLP programme as the set of conclusions which are ultimately warranted, and we present an algorithm for computing it in polynomial space and with an upper bound on complexity equal to P NP . Finally, we propose an efficient and scalable implementation of this algorithm using SAT encodings, and we provide an experimental evaluation when solving test sets of instances with single and multiple preference levels for defeasible knowledge.

Description: In this article, we extend Dung's formal approach from admissibility to less demanding extension semantics allowing arguments in cycles of attacks. We present an acceptance criterion leading to the characterization of three semantics called pairwise cogency , weak cogency and cyclic cogency . Particular game-theoretic protocols allow us to identify winning strategies with extensions in different semantics. Furthermore, an algorithmic characterization of those games exhibits clearly how self-attacking or in odd-length cycles of attack can be rationally managed beyond the limits of admissibility.

Description: Motivation: Random sampling of the solution space has emerged as a popular tool to explore and infer properties of large metabolic networks. However, conventional sampling approaches commonly used do not eliminate thermodynamically unfeasible loops. Results: In order to overcome this limitation, we developed an efficient sampling algorithm called loopless Artificially Centered Hit-and-Run on a Box (ll-ACHRB). This algorithm is inspired by the Hit-and-Run on a Box algorithm for uniform sampling from general regions, but employs the directions of choice approach of Artificially Centered Hit-and-Run. A novel strategy for generating feasible warmup points improved both sampling efficiency and mixing. ll-ACHRB shows overall better performance than current strategies to generate feasible flux samples across several models. Furthermore, we demonstrate that a failure to eliminate unfeasible loops greatly affects sample statistics, in particular the correlation structure. Finally, we discuss recommendations for the interpretation of sampling results and possible algorithmic improvements. Availability and implementation: Source code for MATLAB and OCTAVE including examples are freely available for download at http://www.aibn.uq.edu.au/cssb-resources under Software. Optimization runs can use Gurobi Optimizer (by default if available) or GLPK (included with the algorithm). Contact: lars.nielsen@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Description: A conditional proxy re-encryption (CPRE) scheme enables the proxy to convert a ciphertext from Alice to Bob, if the ciphertext satisfies one condition set by Alice. To improve the issue of more fine-grained on the condition set, Fang, Wang, Ge and Ren proposed a new primitive named Interactive conditional PRE with fine grain policy (ICPRE-FG) in 2011, and left an open problem on how to construct CCA-secure ICPRE-FG without random oracles. In this paper, we answer this open problem affirmatively by presenting a new construction of CCA-secure key-policy attribute-based PRE (KP-ABPRE) without random oracles. In this paper, we enhance the security model of Fang's ICPRE-FG scheme by allowing the adversary to make some extra queries, which do not help them win the game trivially. Finally, we present a CCA-secure KP-ABPRE without random oracles under the 3-weak decisional bilinear Diffie–Hellman inversion(3-wDBDHI) assumption.

Description: The key-insulated signature scheme provides a good method to solve key exposure problem. The key-insulated mechanism has been extended to the identity-based cryptography (IBC) and certificateless cryptography. As a new cryptographic primitive, certificate-based cryptography has unique advantage without key escrow problem in IBC and the complex certificate management problem in traditional PKI. However, certificate-based signature operations are usually performed on insecure environments where the signature key exposure is inevitable. In order to solve this problem, we intro- duce key-insulated idea into certificate-based cryptography and propose the notion and security model of the certificate-based key-insulated signature (CBKIS). In addition, we present a CBKIS scheme that is provably secure in the standard model. Security of scheme is reduced to the hardness of Non Pairing-based Generalized Bilinear DH problem and Many Diffie–Hellman problem. The proposed scheme solves the key exposure problem and improves the security in certificate-based cryptography.

Description: Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of 〉10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its advances is urgently needed. Here, we first summarize the main features of these methods and tools for whole-exome, whole-genome and whole-transcriptome sequencing data. Then, we discuss major challenges like tumor intra-heterogeneity, tumor sample saturation and functionality of synonymous mutations in cancer, all of which may result in false-positive discoveries. Finally, we highlight new directions in studying regulatory roles of noncoding somatic mutations and quantitatively measuring circulating tumor DNA in cancer. This review may help investigators find an appropriate tool for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine.

Description: Recent literature has highlighted the advantages of haplotype association methods for detecting rare variants associated with common diseases. As several new haplotype association methods have been proposed in the past few years, a comparison of new and standard methods is important and timely for guidance to the practitioners. We consider nine methods—Haplo.score, Haplo.glm, Hapassoc, Bayesian hierarchical Generalized Linear Model (BhGLM), Logistic Bayesian LASSO (LBL), regularized GLM (rGLM), Haplotype Kernel Association Test, wei-SIMc-matching and Weighted Haplotype and Imputation-based Tests. These can be divided into two types—individual haplotype-specific tests and global tests depending on whether there is just one overall test for a haplotype region (global) or there is an individual test for each haplotype in the region. Haplo.score is the only method that tests for both; Haplo.glm, Hapassoc, BhGLM and LBL are individual haplotype-specific, while the rest are global tests. For comparison, we also apply a popular collapsing method—Sequence Kernel Association Test (SKAT) and its two variants—SKAT-O (Optimal) and SKAT-C (Combined). We carry out an extensive comparison on our simulated data sets as well as on the Genetic Analysis Workshop (GAW) 18 simulated data. Further, we apply the methods to GAW18 real hypertension data and Dallas Heart Study sequence data. We find that LBL, Haplo.score (global test) and rGLM perform well over the scenarios considered here. Also, haplotype methods are more powerful (albeit more computationally intensive) than SKAT and its variants in scenarios where multiple causal variants act interactively to produce haplotype effects.

Description: The purpose of this article is to inform readers about technical challenges that we encountered when assembling exome sequencing data from the ‘Simplifying Complex Exomes' (SIMPLEXO) consortium—whose mandate is the discovery of novel genes predisposing to breast and ovarian cancers. Our motivation is to share these obstacles—and our solutions to them—as a means of communicating important technical details that should be discussed early in projects involving massively parallel sequencing.

Description: Predictive, preventive, personalized and participatory (P4) medicine is an emerging medical model that is based on the customization of all medical aspects (i.e. practices, drugs, decisions) of the individual patient. P4 medicine presupposes the elucidation of the so-called omic world, under the assumption that this knowledge may explain differences of patients with respect to disease prevention, diagnosis and therapies. Here, we elucidate the role of some selected omics sciences for different aspects of disease management, such as early diagnosis of diseases, prevention of diseases, selection of personalized appropriate and optimal therapies based on molecular profiling of patients. After introducing basic concepts of P4 medicine and omics sciences, we review some computational tools and approaches for analysing selected omics data, with a special focus on microarray and mass spectrometry data, which may be used to support P4 medicine. Some applications of biomarker discovery and pharmacogenomics and some experiences on the study of drug reactions are also described.

Description: A wide variety of large-scale data have been produced in bioinformatics. In response, the need for efficient handling of biomedical big data has been partly met by parallel computing. However, the time demand of many bioinformatics programs still remains high for large-scale practical uses because of factors that hinder acceleration by parallelization. Recently, new generations of storage devices have emerged, such as NAND flash-based solid-state drives (SSDs), and with the renewed interest in near-data processing, they are increasingly becoming acceleration methods that can accompany parallel processing. In certain cases, a simple drop-in replacement of hard disk drives by SSDs results in dramatic speedup. Despite the various advantages and continuous cost reduction of SSDs, there has been little review of SSD-based profiling and performance exploration of important but time-consuming bioinformatics programs. For an informative review, we perform in-depth profiling and analysis of 23 key bioinformatics programs using multiple types of devices. Based on the insight we obtain from this research, we further discuss issues related to design and optimize bioinformatics algorithms and pipelines to fully exploit SSDs. The programs we profile cover traditional and emerging areas of importance, such as alignment, assembly, mapping, expression analysis, variant calling and metagenomics. We explain how acceleration by parallelization can be combined with SSDs for improved performance and also how using SSDs can expedite important bioinformatics pipelines, such as variant calling by the Genome Analysis Toolkit and transcriptome analysis using RNA sequencing. We hope that this review can provide useful directions and tips to accompany future bioinformatics algorithm design procedures that properly consider new generations of powerful storage devices.

Description: This article is about busting loops in abstract argumentation networks. We propose several approaches to how to deal with networks which have loops (such as even or odd cycles) and get new extensions which are ‘in’, ‘out’ extensions, with no undecided elements.

Description: Current approaches for giving semantics to abstract argumentation frameworks dismiss altogether any possibility of having conflicts among accepted arguments by requiring that the latter should be ‘conflict free’. In reality, however, contradictory phenomena coexist, or it may happen that one cannot make a choice between conflicting indications but still would like to keep track to all of them. For this purpose we introduce in this article a new kind of argumentation semantics, called ‘conflict-tolerant’, in which all the accepted arguments must be justified (in the sense that each one of them can be defended), but some of them may still attack each other. In terms of graphical representation of argumentation systems, where attacks are represented by directed edges, this means that the possibility of accepting ‘loops’ of arguments is not automatically ruled out without any further considerations. To provide conflict-tolerant semantics, we enhance the two standard approaches for defining coherent (conflict-free) semantics for argumentation frameworks. The extension-based approach is generalized by relaxing the ‘conflict-freeness’ requirement of the chosen sets of arguments, and the three-valued labelling approach is replaced by a four-valued labelling system that allows to capture mutual attacks among accepted arguments. We show that our setting is not a substitute of standard (conflict-free) semantics, but rather a generalized framework that accommodates both conflict-free and conflict-tolerant semantics. Moreover, the one-to-one relationship between extensions and labellings of conflict-free semantics is carried on to a similar correspondence between the extended approaches for providing conflict-tolerant semantics. Thus, in our setting as well, these are essentially two points of views for the same thing.

Description: A special case of loops in argumentation are self-attacking arguments. While their role with respect to the ontological nature of argumentation is controversially discussed, their presence (or absence) in the abstract setting of Dung-style argumentation frameworks seems to be less crucial for semantics or fundamental properties. There are, however, a few exceptions where self-attacking arguments have essential influence. One such exception concerns characterizations of (strong) equivalence notions between argumentation frameworks. Different notions of equivalence have recently been proposed in the literature and several characterization results for different semantics have been obtained. In this article, we will survey the current state of this research direction with a particular emphasis on the effect of (dis)allowing self-conflicting arguments. We also provide some novel results for stage, eager and naive semantics in order to present a full classification of ten prominent semantics and four equivalence notions.

Description: Results: Here, we present a comprehensive analysis on the reproducibility of computational characterization of genomic variants using high throughput sequencing data. We reanalyzed the same datasets twice, using the same tools with the same parameters, where we only altered the order of reads in the input (i.e. FASTQ file). Reshuffling caused the reads from repetitive regions being mapped to different locations in the second alignment, and we observed similar results when we only applied a scatter/gather approach for read mapping—without prior shuffling. Our results show that, some of the most common variation discovery algorithms do not handle the ambiguous read mappings accurately when random locations are selected. In addition, we also observed that even when the exact same alignment is used, the GATK HaplotypeCaller generates slightly different call sets, which we pinpoint to the variant filtration step. We conclude that, algorithms at each step of genomic variation discovery and characterization need to treat ambiguous mappings in a deterministic fashion to ensure full replication of results. Availability and Implementation: Code, scripts and the generated VCF files are available at DOI:10.5281/zenodo.32611. Contact: calkan@cs.bilkent.edu.tr Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Animals from worms and insects to birds and mammals show distinct body plans; however, the embryonic development of diverse body plans with tissues and organs within is controlled by a surprisingly few signaling pathways. It is well recognized that combinatorial use of and dynamic interactions among signaling pathways follow specific logic to control complex and accurate developmental signaling and patterning, but it remains elusive what such logic is, or even, what it looks like. Results: We have developed a computational model for Drosophila eye development with innovated methods to reveal how interactions among multiple pathways control the dynamically generated hexagonal array of R8 cells. We obtained two novel findings. First, the coupling between the long-range inductive signals produced by the proneural Hh signaling and the short-range restrictive signals produced by the antineural Notch and EGFR signaling is essential for generating accurately spaced R8s. Second, the spatiotemporal orders of key signaling events reveal a robust pattern of lateral inhibition conducted by Ato-coordinated Notch and EGFR signaling to collectively determine R8 patterning. This pattern, stipulating the orders of signaling and comparable to the protocols of communication, may help decipher the well-appreciated but poorly defined logic of developmental signaling. Availability and implementation: The model is available upon request. Contact: hao.zhu@ymail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The growing amount of regulatory data from the ENCODE, Roadmap Epigenomics and other consortia provides a wealth of opportunities to investigate the functional impact of single nucleotide polymorphisms (SNPs). Yet, given the large number of regulatory datasets, researchers are posed with a challenge of how to efficiently utilize them to interpret the functional impact of SNP sets. Results: We developed the GenomeRunner web server to automate systematic statistical analysis of SNP sets within a regulatory context. Besides defining the functional impact of SNP sets, GenomeRunner implements novel regulatory similarity/differential analyses, and cell type-specific regulatory enrichment analysis. Validated against literature- and disease ontology-based approaches, analysis of 39 disease/trait-associated SNP sets demonstrated that the functional impact of SNP sets corresponds to known disease relationships. We identified a group of autoimmune diseases with SNPs distinctly enriched in the enhancers of T helper cell subpopulations, and demonstrated relevant cell type-specificity of the functional impact of other SNP sets. In summary, we show how systematic analysis of genomic data within a regulatory context can help interpreting the functional impact of SNP sets. Availability and Implementation: GenomeRunner web server is freely available at http://www.integrativegenomics.org/ . Contact: mikhail.dozmorov@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Adverse drug reactions (ADRs) are a central consideration during drug development. Here we present a machine learning classifier to prioritize ADRs for approved drugs and pre-clinical small-molecule compounds by combining chemical structure (CS) and gene expression (GE) features. The GE data is from the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 dataset that measured changes in GE before and after treatment of human cells with over 20 000 small-molecule compounds including most of the FDA-approved drugs. Using various benchmarking methods, we show that the integration of GE data with the CS of the drugs can significantly improve the predictability of ADRs. Moreover, transforming GE features to enrichment vectors of biological terms further improves the predictive capability of the classifiers. The most predictive biological-term features can assist in understanding the drug mechanisms of action. Finally, we applied the classifier to all 〉20 000 small-molecules profiled, and developed a web portal for browsing and searching predictive small-molecule/ADR connections. Availability and Implementation: The interface for the adverse event predictions for the 〉20 000 LINCS compounds is available at http://maayanlab.net/SEP-L1000/ . Contact: avi.maayan@mssm.edu Supplementary information : Supplementary data are available at Bioinformatics online.

Description: Motivation: Environmental dissemination of antibiotic resistance genes (ARGs) has become an increasing concern for public health. Metagenomics approaches can effectively detect broad profiles of ARGs in environmental samples; however, the detection and subsequent classification of ARG-like sequences are time consuming and have been severe obstacles in employing metagenomic methods. We sought to accelerate quantification of ARGs in metagenomic data from environmental samples. Results: A Structured ARG reference database (SARG) was constructed by integrating ARDB and CARD, the two most commonly used databases. SARG was curated to remove redundant sequences and optimized to facilitate query sequence identification by similarity. A database with a hierarchical structure (type-subtype-reference sequence) was then constructed to facilitate classification (assigning ARG-like sequence to type, subtype and reference sequence) of sequences identified through similarity search. Utilizing SARG and a previously proposed hybrid functional gene annotation pipeline, we developed an online pipeline called ARGs-OAP for fast annotation and classification of ARG-like sequences from metagenomic data. We also evaluated and proposed a set of criteria important for efficiently conducting metagenomic analysis of ARGs using ARGs-OAP. Availability and Implementation: Perl script for ARGs-OAP can be downloaded from https://github.com/biofuture/Ublastx_stageone . ARGs-OAP can be accessed through http://smile.hku.hk/SARGs . Contact: zhangt@hku.hk or tiedjej@msu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Visualizing genomic data in chromosomal context can help detecting errors in data processing and may suggest new hypotheses to be tested. Here, we report a new tool for displaying large and diverse genomic data along chromosomes. The software is implemented in R so that visualization can be easily integrated with its numerous packages for processing genomic data. It supports simultaneous visualization of multiple tracks of data. Large genomic regions such as QTLs or synteny tracts may be shown along histograms of number of genes, genetic variants, or any other type of genomic element. Tracks can also contain values for continuous or categorical variables and the user can choose among points, connected lines, colored segments, or histograms for representing data. chromPlot takes data from tables in data.frame in GRanges formats. The information necessary to draw chromosomes for mouse and human is included with the package. For other organisms, chromPlot can read Gap and cytoBandIdeo tables from the UCSC Genome Browser. We present common use cases here, and a full tutorial is included as the package’s vignette. Availability and Implementation: chromPlot is distributed under a GLP2 licence at http://www.bioconductor.org . Contact: raverdugo@u.uchile.cl Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a small memory usage. The new version, called BLESS 2, has an error correction algorithm that is more accurate than BLESS, and the algorithm has been parallelized using hybrid MPI and OpenMP programming. BLESS 2 was compared with five top-performing tools, and it was found to be the fastest when it was executed on two computing nodes using MPI, with each node containing twelve cores. Also, BLESS 2 showed at least 11% higher gain while retaining the memory efficiency of the previous version for large genomes. Availability and implementation: Freely available at https://sourceforge.net/projects/bless-ec Contact: dchen@illinois.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation. Results: In this work, we proposed a novel design of DNNs for this task. We trained a pixel classifier that operates on raw pixel intensities with no preprocessing to generate probability values for each pixel being a membrane or not. Although the use of neural networks in image segmentation is not completely new, we developed novel insights and model architectures that allow us to achieve superior performance on EM image segmentation tasks. Our submission based on these insights to the 2D EM Image Segmentation Challenge achieved the best performance consistently across all the three evaluation metrics. This challenge is still ongoing and the results in this paper are as of June 5, 2015. Availability and Implementation : https://github.com/ahmed-fakhry/dive Contact : sji@eecs.wsu.edu

Description: : Hilbert curves enable high-resolution visualization of genomic data on a chromosome- or genome-wide scale. Here we present the HilbertCurve package that provides an easy-to-use interface for mapping genomic data to Hilbert curves. The package transforms the curve as a virtual axis, thereby hiding the details of the curve construction from the user. HilbertCurve supports multiple-layer overlay that makes it a powerful tool to correlate the spatial distribution of multiple feature types. Availability and implementation: The HilbertCurve package and documentation are freely available from the Bioconductor project: http://www.bioconductor.org/packages/devel/bioc/html/HilbertCurve.html Contact: m.schlesner@dkfz.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The sequences among subgenomes in a polyploid species have high similarity, making it difficult to design genome-specific primers for sequence analysis. Results: We present GSP, a web-based platform to design genome-specific primers that distinguish subgenome sequences in a polyploid genome. GSP uses BLAST to extract homeologous sequences of the subgenomes in existing databases, performs a multiple sequence alignment, and design primers based on sequence variants in the alignment. An interactive primers diagram, a sequence alignment viewer and a virtual electrophoresis are displayed as parts of the primer design result. GSP also designs specific primers from multiple sequences uploaded by users. Availability and implementation: GSP is a user-friendly and efficient web platform freely accessible at http://probes.pw.usda.gov/GSP . Source code and command-line application are available at https://github.com/bioinfogenome/GSP . Contacts: yong.gu@ars.usda.gov or devin.coleman-derr@ars.usda.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : The prediction of protein–protein complexes from the structures of unbound components is a challenging and powerful strategy to decipher the mechanism of many essential biological processes. We present a user-friendly protein–protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein–protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein–protein binding conformations that can be further refined with more computationally demanding strategies. Availability and Implementation: The server is free and open to all users with no login requirement at http://frodock.chaconlab.org Contact: pablo@chaconlab.org Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : XIBD performs pairwise relatedness mapping on the X chromosome using dense single nucleotide polymorphism (SNP) data from either SNP chips or next generation sequencing data. It correctly accounts for the difference in chromosomal numbers between males and females and estimates global relatedness as well as regions of the genome that are identical by descent (IBD). XIBD also generates novel graphical summaries of all pairwise IBD tracts for a cohort making it very useful for disease locus mapping. Availability and implementation: XIBD is written in R/Rcpp and executed from shell scripts that are freely available from http://bioinf.wehi.edu.au/software/XIBD along with accompanying reference datasets. Contact: henden.l@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Several approaches to the region-based association analysis of quantitative traits have recently been developed and successively applied. However, no software package has been developed that implements all of these approaches for either independent or structured samples. Here we introduce FREGAT (Family REGional Association Tests), an R package that can handle family and population samples and implements a wide range of region-based association methods including burden tests, functional linear models, and kernel machine-based regression. FREGAT can be used in genome/exome-wide region-based association studies of quantitative traits and candidate gene analysis. FREGAT offers many useful options to empower its users and increase the effectiveness and applicability of region-based association analysis. Availability and Implementation: https://cran.r-project.org/web/packages/FREGAT/index.html Supplementary Information: Supplementary data are available at Bioinformatics Online. Contact: belon@bionet.nsc.ru

Description: Motivation: There is a growing need in bioinformatics for easy-to-use software implementations of algorithms that are usable across platforms. At the same time, reproducibility of computational results is critical and often a challenge due to source code changes over time and dependencies. Results: The approach introduced in this paper addresses both of these needs with AlgoRun, a dedicated packaging system for implemented algorithms, using Docker technology. Implemented algorithms, packaged with AlgoRun, can be executed through a user-friendly interface directly from a web browser or via a standardized RESTful web API to allow easy integration into more complex workflows. The packaged algorithm includes the entire software execution environment, thereby eliminating the common problem of software dependencies and the irreproducibility of computations over time. AlgoRun-packaged algorithms can be published on http://algorun.org , a centralized searchable directory to find existing AlgoRun-packaged algorithms. Availability and implementation: AlgoRun is available at http://algorun.org and the source code under GPL license is available at https://github.com/algorun Contact: laubenbacher@uchc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: In this paper, we propose a privacy-preserving reservation system for electric vehicles (EV) charging stations. Due to the short driving range of EV, frequent charging is necessary. A mechanism for charging station reservation for EV owners is desirable. Our proposed system allows the vehicle owner to reserve a number of charging stations along the intended route at different time-slots. Yet it is secure against misuse such that a user can only hold a limited number of reservations simultaneously. More importantly, our system can provide privacy for users. The charging station does not know the identity of the user who has reserved it. Thus location privacy can be protected. We demonstrate the practicality of our system with a prototype implementation on a smart phone. Finally, we also provide a security proof to show that our system is secure under well-known computational assumptions.

Description: A blackbox traceable Attribute-Based Encryption (ABE) can identify a malicious user called traitor, which created a decryption box with respect to an attribute set (respectively, access policy), out of all the users who share the same attribute set (respectively, access policy). However, none of the existing traceable ABE schemes can also support revocation and large attribute universe, that is, being able to revoke compromised keys, and can take an exponentially large number of attributes. In this paper, we formalize the definitions and security models, and propose constructions of both Ciphertext-Policy ABE and Key-Policy ABE that support (i) public and fully collusion-resistant blackbox traceability, (ii) revocation, (iii) large universe and (iv) any monotonic access structures as policies (i.e. high expressivity). We also show that the schemes are secure and blackbox traceable in the standard model against selective adversaries.

Description: White-box cryptography aims at implementing a cipher to protect its key from being extracted in an untrusted environment, where the attacker has full access to the execution of the cryptographic software. In 2002, Chow et al. proposed the original white-box implementation of AES. Afterwards, various white-box implementations were presented. However, they were all badly broken because of a weakness of the implemented cryptographic algorithms: every parameter of the cryptographic operations is fixed except the round keys. In this paper, we present an AES-like cipher based on key-dependent S-boxes. The new cipher is designed to meet the design criteria of AES and hence provides a security level comparable to AES to resist black-box attacks. Moreover, we present a white-box implementation for our AES-like cipher, which is sufficient to withstand existing white-box attacks.

Description: Identity-based encryption (IBE) has many appealing applications. However, some traditional IBE schemes may not be secure in the real world due to the side-channel attacks. Leakage-resilient cryptography can capture these attacks by modeling information leakage that adversary can access. In this paper, we apply a hash proof technique in the existing CCA-secure variant of the Gentry's IBE scheme to construct a new leakage-resilient IBE scheme in the bounded-leakage model. The proposed scheme is more computationally efficient than the original Alwen et al. 's leakage-resilient IBE scheme. It enjoys a shorter key (public/secret key) length, and a higher relative key leakage ratio. The new leakage-resilient scheme is proved semantically secure against adaptive chosen ciphertext attack in the standard model under the truncated augmented bilinear Diffie-Hellman exponent ( $q$ -TABDHE) assumption.

Description: Motivation: Genome browsers that support fast navigation through vast datasets and provide interactive visual analytics functions can help scientists achieve deeper insight into biological systems. Toward this end, we developed Integrated Genome Browser (IGB), a highly configurable, interactive and fast open source desktop genome browser. Results: Here we describe multiple updates to IGB, including all-new capabilities to display and interact with data from high-throughput sequencing experiments. To demonstrate, we describe example visualizations and analyses of datasets from RNA-Seq, ChIP-Seq and bisulfite sequencing experiments. Understanding results from genome-scale experiments requires viewing the data in the context of reference genome annotations and other related datasets. To facilitate this, we enhanced IGB’s ability to consume data from diverse sources, including Galaxy, Distributed Annotation and IGB-specific Quickload servers. To support future visualization needs as new genome-scale assays enter wide use, we transformed the IGB codebase into a modular, extensible platform for developers to create and deploy all-new visualizations of genomic data. Availability and implementation: IGB is open source and is freely available from http://bioviz.org/igb . Contact: aloraine@uncc.edu

Description: Motivation: Single Molecule Real-Time (SMRT) sequencing technology and Oxford Nanopore technologies (ONT) produce reads over 10 kb in length, which have enabled high-quality genome assembly at an affordable cost. However, at present, long reads have an error rate as high as 10–15%. Complex and computationally intensive pipelines are required to assemble such reads. Results: We present a new mapper, minimap and a de novo assembler, miniasm, for efficiently mapping and assembling SMRT and ONT reads without an error correction stage. They can often assemble a sequencing run of bacterial data into a single contig in a few minutes, and assemble 45-fold Caenorhabditis elegans data in 9 min, orders of magnitude faster than the existing pipelines, though the consensus sequence error rate is as high as raw reads. We also introduce a pairwise read mapping format and a graphical fragment assembly format, and demonstrate the interoperability between ours and current tools. Availability and implementation: https://github.com/lh3/minimap and https://github.com/lh3/miniasm Contact: hengli@broadinstitute.org Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Alternative splicing represents a prime mechanism of post-transcriptional gene regulation whose misregulation is associated with a broad range of human diseases. Despite the vast availability of transcriptome data from different cell types and diseases, bioinformatics-based surveys of alternative splicing patterns remain a major challenge due to limited availability of analytical tools that combine high accuracy and rapidity. Results: We describe here a novel junction-centric method, jSplice, that enables de novo extraction of alternative splicing events from RNA-sequencing data with high accuracy, reliability and speed. Application to clear cell renal carcinoma (ccRCC) cell lines and 65 ccRCC patients revealed experimentally validatable alternative splicing changes and signatures able to prognosticate ccRCC outcome. In the aggregate, our results propose jSplice as a key analytic tool for the derivation of cell context-dependent alternative splicing patterns from large-scale RNA-sequencing datasets. Availability and implementation: jSplice is a standalone Python application freely available at http://www.mhs.biol.ethz.ch/research/krek/jsplice . Contact: wilhelm.krek@biol.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. Results: We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ~90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in 〉 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. Availability and Implementation: An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC . Contact: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Biological network querying is a problem requiring a considerable computational effort to be solved. Given a target and a query network, it aims to find occurrences of the query in the target by considering topological and node similarities (i.e. mismatches between nodes, edges, or node labels). Querying tools that deal with similarities are crucial in biological network analysis because they provide meaningful results also in case of noisy data. In addition, as the size of available networks increases steadily, existing algorithms and tools are becoming unsuitable. This is rising new challenges for the design of more efficient and accurate solutions. Results: This paper presents APPAGATO , a stochastic and parallel algorithm to find approximate occurrences of a query network in biological networks. APPAGATO handles node, edge and node label mismatches. Thanks to its randomic and parallel nature, it applies to large networks and, compared with existing tools, it provides higher performance as well as statistically significant more accurate results. Tests have been performed on protein–protein interaction networks annotated with synthetic and real gene ontology terms. Case studies have been done by querying protein complexes among different species and tissues. Availability and implementation: APPAGATO has been developed on top of CUDA-C ++ Toolkit 7.0 framework. The software is available online http://profs.sci.univr.it/~bombieri/APPAGATO . Contact: rosalba.giugno@univr.it Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : We introduce SharpViSu, an interactive open-source software with a graphical user interface, which allows performing processing steps for localization data in an integrated manner. This includes common features and new tools such as correction of chromatic aberrations, drift correction based on iterative cross-correlation calculations, selection of localization events, reconstruction of 2D and 3D datasets in different representations, estimation of resolution by Fourier ring correlation, clustering analysis based on Voronoi diagrams and Ripley’s functions. SharpViSu is optimized to work with eventlist tables exported from most popular localization software. We show applications of these on single and double-labelled super-resolution data. Availability and implementation: SharpViSu is available as open source code and as compiled stand-alone application under https://github.com/andronovl/SharpViSu . Contact: klaholz@igbmc.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : A gene tree-species tree reconciliation explains the evolution of a gene tree within the species tree given a model of gene-family evolution. We describe ecceTERA, a program that implements a generic parsimony reconciliation algorithm, which accounts for gene duplication, loss and transfer (DTL) as well as speciation, involving sampled and unsampled lineages, within undated, fully dated or partially dated species trees. The ecceTERA reconciliation model and algorithm generalize or improve upon most published DTL parsimony algorithms for binary species trees and binary gene trees. Moreover, ecceTERA can estimate accurate species-tree aware gene trees using amalgamation. Availability and implementation : ecceTERA is freely available under http://mbb.univ-montp2.fr/MBB/download_sources/16__ecceTERA and can be run online at http://mbb.univ-montp2.fr/MBB/subsection/softExec.php?soft=eccetera . Contact: celine.scornavacca@umontpellier.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : The popularity of using NMR spectroscopy in metabolomics and natural products has driven the development of an array of NMR spectral analysis tools and databases. Particularly, web applications are well used recently because they are platform-independent and easy to extend through reusable web components. Currently available web applications provide the analysis of NMR spectra. However, they still lack the necessary processing and interactive visualization functionalities. To overcome these limitations, we present NMRPro, a web component that can be easily incorporated into current web applications, enabling easy-to-use online interactive processing and visualization. NMRPro integrates server-side processing with client-side interactive visualization through three parts: a python package to efficiently process large NMR datasets on the server-side, a Django App managing server-client interaction, and SpecdrawJS for client-side interactive visualization. Availability and implementation: Demo and installation instructions are available at http://mamitsukalab.org/tools/nmrpro/ Contact: mohamed@kuicr.kyoto-u.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

Description: A cascaded Organic Rankine Cycle (ORC) with scroll expanders is investigated in this paper, the system performances under various configurations are evaluated and the effect of superheating on the system efficiency is clarified. The efficiency of two-stage ORC system is 38.9% higher than that of single-stage system when R245fa is used as the working fluid, while the efficiency of two-stage ORC system is 10% lower than that of single stage when R134a is adopted. The specific work of single-stage ORC system with R245fa increases linearly with the degree of superheat. There is an optimal superheated degree for the system output power and efficiency, which is 35 K for the expansion ratio of 3.5 and 45 K for the expansion ratio of 5.

Description: This article demonstrates a study on finite-time thermodynamic assessment and analysis of a Stirling heat engine. Finite-time thermodynamics is performed to specify the net thermal efficiency and power output of the Stirling system with finite-rate heat transfer, regenerative heat loss, conductive thermal bridging loss and finite regeneration process time. The model investigates effects of the inlet temperature of the heat source, the volumetric ratio of the engine, effectiveness of heat exchangers and heat capacitance rates on the net power output and thermal efficiency of the engine. Output power of the Stirling engine is maximized under two optimization scenarios. In the first scenario, the higher working temperature of the Stirling engine is considered as a decision design parameter (decision variable) while in the second scenario, in addition to the higher working temperature, the temperature ratio of the engine is also considered as a design parameter. Furthermore, the thermal efficiency of the cycle corresponding to the magnitude of the maximized power of the engine is evaluated. Finally, sensitivities of results towards shift in the thermal parameters of the engine are studied.

Description: Vapour compression refrigeration-based air conditioners are being used for comfort cooling in residences, offices and commercial buildings in many countries throughout the world. These systems consume substantial power and energy and produce harmful effect on environment by damaging ozone layer. This article presents an analytical evaluation of energy saving potential of an indirect evaporative cooler for summer months in Indian climates. Three climates likely to be suitable for indirect evaporative cooling, namely composite, hot and dry and moderate, have been selected for this purpose. The monthly average environmental data for three Indian cities namely Delhi, Jodhpur and Bangalore representing three different climates were used for this study. Summer month—May was selected for the study. It has been found that in order to produce same cooling effect under the same climatic conditions, the power needed by indirect evaporative cooler to be about 55% less than that needed by a conventional air conditioner. The performance of an indirect evaporative cooler in the climates, hot and dry and composite, has been found to be almost similar. Thus, substantial energy can be saved by using this alternative in summer months.

Description: A MATLAB-based computer model to design a novel directly absorbing receiver system (DARS) for concentrating solar collectors employing nanofluid-based solar radiation volumetric absorption is presented. Graphene and aluminum nanosphere-based suspensions in Therminol VP-1 were simulated to identify the optimum thermo-geometric configuration of a DARS comprising a transparent all glass tubular absorber. Several particle concentrations were simulated scrutinizing the optical response of the two colloidal dispersions to yield a minimum supply temperature of 250°C; further investigated are the implications of fluid flow velocity upon system yield. The resulting temperature fields and geometric dimensions of the DARS are predicted. Findings demonstrate that the DARS is able to deliver heat at ~265°C with a receiver tube diameter of 5 mm opposed to commercially available 70-mm diameter metallic absorbers.

Description: Distributed power generation (DPG) based on organic Rankine cycle offers potential in the effective use of energy from low grade heat sources up to 200°C. In this regard, developing an effective expander plays a major role in determining the overall cycle efficiency. In this work mean-line modeling and CFD techniques are employed to develop a small-scale radial turbine for DPG systems with a power output of ~5 kWe. A parametric study is carried out using the mean-line approach to investigate the effects of key input parameters such as operating conditions, velocity ratio, rotational speed and rotor flow angles on the turbine rotor inlet diameter and overall performance. Results from the mean-line approach show that in order to achieve high power output, inlet total temperature, mass flow rate and pressure ratio should be increased. However, for reducing the rotor inlet diameter the velocity ratio should be decreased. CFD technique is then used to assess the flow field and to improve the blade loading by modification of blade angle distribution. CFD is also used to determine the minimum number of rotor blades and the results show that the value suggested by mean-line modeling overestimates this parameter. By using these two approaches a wide range of design configurations are explored and the most effective design is identified to be with specific diameter of 4.83 (rotor inlet diameter of 0.0787 m), specific speed of 0.433 (rotational speed of 55 000 rpm), 10 blades and output power of 4.662 kW.

Description: Concerns about greenhouse gases as well as the price and security of oil supply have acted as a spur to sustainable automobile development. The hydrogen fuel cells electric vehicle (HFCEV) is generally recognised by leading automobile manufacturers and scientists as one of the optimum technologies for long-term future low carbon vehicle. In a typical HFCEV power train, a DC–DC converter is required to balance the voltage difference between the fuel cells (FCs) stack and batteries. However, research shows that a considerable amount of energy generated by the hydrogen FCs stack is deplete during this conversion process as heat. This experiment aims to improve the power train efficiency by eliminating the DC–DC converter by finding the best combination of FC stack and batteries, matching the size and capacity of the electrical components.

Description: In this communication, a comprehensive thermodynamic model for exergy analysis of a passive solar distillation system is presented. Temperatures of basin-liner, saline water body and inner and outer glass cover are estimated theoretically with the help of a computer program using a set of typical design and operating parameters. Energy and exergy analysis of a single-effect, single-slope horizontal passive solar still has been carried out under climatic conditions of India. It has been shown that the passive solar still can produce 4.17 l/m 2 of freshwater daily. Energy and exergy efficiency of the solar still are 30.42 and 4.93%, respectively. Causes, quantity and place of exergy destruction have also been explored for further research and improvement in the design and performance of solar stills. Exergy destruction or irreversibility in the process of each component, i.e. basin-liner, saline water body and glass cover, has been evaluated as 3353, 1633 and 362 W/m 2 , respectively, corresponding to the total solar exergy input of 6958 W/m 2 on a typical day. Their corresponding exergy efficiencies are found to be 3.91, 17.67 and 42.36%. The global exergy efficiency of the solar still is also estimated as 23.14%, taking these exergy destructions into account. The basin-liner is identified as the component around which there is highest possibility of improvement.

Description: A comparison is presented between experimental and numerical results regarding the operation of a capillary pumped loop evaporator. Two cylindrical evaporators were tested, with different heated porous lengths, 20 and 40 mm, respectively. Both have 22 mm external diameter, 9 mm porous thickness and 80 mm porous length. The working liquid was water. The loop was made from copper tubes and the evaporator from copper porous wick covered with aluminum with grooves formed in the inner surface. All tests took place on a horizontal level using heat load applied to the evaporator surface from an 85-W electric resistance. The experimental measurements were compared with the predictions of a three-dimensional CFD model of the evaporator and were found to be in satisfactory agreement. For the 20-mm wick heated length evaporator CFD model with water initial temperature of 20°C the divergence with the experimental pressure drop mean value was 0 Pa for volume flow rates between 0.4 and 0.6 l/min and 50 Pa for the rest of the values. For 30°C the divergence was 0 Pa 〈0.4 l/min and 50 Pa for larger flow rates. Moreover, for 40°C the difference was up to 50 Pa from 0 to 0.9 l/min. In every case predictions were below the wick capillary limit. The computed outflow temperature presented a maximum difference of 1.5% compared with the experimental data, which is very satisfying. On the other hand, the predictions of the evaporator CFD model with a 40-mm wick heated length were even better.

Description: A new CO 2 cryogenic capture and liquefaction system has been proposed previously in order to separate CO 2 from exhausted gases and make it as a resource for industry. This system combines CO 2 cryogenic capture with N 2 /O 2 separation together. Its energy consumption is lower than the traditional amine solution capture process as theoretical analysis. In this study, the simulation of the proposed system with several improvements was carried out aiming to reduce the energy consumption further. Many heat exchangers were introduced and the heat exchanger arrangements were optimized to recycle the refrigeration capacity from the returned N 2 after the N 2 /O 2 separation. The discharge pressure of mixture gas from the compressor was reduced from 10 to 3.493 MPa. The simulation results showed that the compression work could be greatly reduced and the energy consumption of CO 2 capture in this new system after these improvements reached 2.884 GJ/ton CO 2 . The new system is promising because not only liquid or solid CO 2 could be produced but also N 2 and O 2 could be separated.

Description: Learning by doing, or learning through market experience, reduces costs for energy production technologies. This phenomenon is modelled by using experience curves which reflect the changes in the cost of the technology as it becomes increasingly used. This article calculates the Spanish photovoltaic (PV) learning curve over the period 2001–12 by using cost data from the PV sector itself (installers, distributors and even engineers) and determines the accuracy of the obtained progress ratio by using both the coefficient of determination R 2 and also the error PR , which is directly determined from fitting the data. The results show a curve with a strong structural change in the speed of cost reduction in October 2009.

Description: Important advances have been made in solar water desalination technology but their wide application is restricted by relatively high capital and running costs. Until recently, solar concentrator collectors had usually been employed to distill water in compact desalination systems. Currently, it is possible to replace these collectors by the more efficient evacuated tube collectors, which are now widely available on the market at lower prices. This paper describes the results of experimental and theoretical investigations of the operation of a novel small-scale solar water desalination technology using the psychometric humidification and dehumidification process coupled with a heat pipe evacuated tube solar collector with an aperture area of ~1.73 m 2 . Solar radiation during spring in the Middle East was simulated by an array of halogen floodlights. A synthetic brackish water solution was used for the tests and its total dissolved solids (TDSs) and electrical conductivity were measured. A mathematical model was developed to describe the system's operation. A computer program was written to solve the system of governing equations to perform the theoretical calculations of the humidification and dehumidification processes. The experimental and theoretical values for the total daily distillate output were found to be closely correlated. The test results demonstrate that, at temperatures of 55–60°C, the system produces ~5–6 kg/h of clean water with a high desalination efficiency. Following the experimental calibration of the mathematical model, it was demonstrated that the performance of the system could be improved to produce a considerably higher amount of fresh water.

Description: Phase change material (PCM)-filled glass window was suitable for absorbing or releasing more heat than conventional glass window. Comparisons of thermal performance between PCM-filled glass windows and insulated glass windows (double glass windows filled with dry air and surrounded by sealing strips) were presented in this paper. A 3D unsteady model was built in FLUENT to obtain the internal and external surface temperature fluctuations of these windows in 48 h. Compared with insulated glass windows, thermal performance (especially the thermal regulation effect) of double glass windows filled with Na 2 SO 4 ·10H 2 O was quite satisfactory in sunny days of summer, while double glass windows filled with CaCl 2 ·6H 2 O had a better thermal performance in overcast and rainy days of summer. Because the phase change temperature of these PCM is higher than the ambient temperature in winter, the thermal regulation effects of them were not as good as expected.

Description: Optimization of heat exchanger network is attributed to improving the process industrial energy utilization ratio. Energy consumption reduction plays an important role in the low-carbon economic development. Several synthesis approaches for heat exchanger network have been proposed and extended during the last three decades. With the evolution of the computer technology, the simultaneous synthesis method via mathematic programming attracts a great deal of attention worldwide. However, some difficulties still need to be overcome, for instance, model simplification and computational complexity. In this work, the simultaneous stage-wise synthesis model without the assumption of isothermal mixing is presented and implemented using effective initialization strategies and a novel two-level algorithm. Three case studies illustrated the better performance of the initialization strategies and two-level algorithm for heat exchanger network synthesis problems, considering non-isothermal mixing.

Description: Atmospheric carbon dioxide is one of the primary greenhouse gases on earth and its continuous emission by manmade activities is leading to a rise in atmospheric temperature. On the other hand, various natural phenomena exist that contribute to the sequestration of atmospheric carbon dioxide, i.e. its capture and long-term storage. These phenomena include oceanic, geological and chemical processes happening on earth. In addition to the above-mentioned nonbiological methods, various biological methods viz. soil carbon sequestration and phytosequestration have also been contributing to fixation of atmospheric carbon. Phytosequestration is mainly performed by several photosynthetic mechanisms such as C 3 , C 4 and crassulacean acid metabolism (CAM) pathways of plants, carboxysomes of cyanobacteria and pyrenoids of microalgae. For an effective mitigation of global climate change, it is required to stabilize the CO 2 concentration to viable levels. It requires various permutations and combinations of naturally existing and engineering strategies. Although numerous strategies are in commodious use in the present times, the issues of sustainability and long-term stability still exist. We present an overview of the natural and manmade biological and nonbiological processes used today to reduce atmospheric CO 2 levels and discuss the scope and limitations of each of them.

Description: A conventional natural convection flat plate solar collector needs to be placed at an incline to the horizontal and exposed to the sun in order for the solar hot water heater system to work. This arrangement is satisfactory where there is ample roof top space to locate the collector and storage tank. In a high-rise apartment, space is at a premium and also the hot-water recticulation requires long lengths of piping to distribute the hot water supply to the individual apartment. Most every modern high-rise apartment has a balcony facing outward from the wall structure. Balcony-type solar water heaters (SWHs) are catching up fast in China. Their performance would depend on collector and storage tank designs and sizes, weather conditions (solar radiation intensity and ambient temperature) and direction in which the balconies are facing. This article compares the outdoor performance of two SWH systems incorporating the evacuated glass U-tube solar collectors operating under natural convection. The panels were tested in both the vertical and inclined positions using the same tank but at different times of the year. It was found that the inclined panel system performed better than the system with the vertical panel system.

Description: The Construction Industry Council (CIC) Zero-Carbon Building is a net zero-carbon building that was designed for local hot and humid climate of sub-tropical Hong Kong. Over 80 sustainability features of the architecture and building systems have considered the life-cycle carbon emissions, including the embodied carbon of construction materials, emissions associated with the construction process, the 50-years of operation and decommission of the building. The total life-cycle carbon emission was off-set by on-site renewable energy generated by photovoltaics (PV) and bio-diesel combined cooling heating and power (CCHP) system. To optimise the design, a series of climate-responsive strategies on passive architecture were applied to the construction of the building. These include the high-performance facade, effective air tightness and optimised window design that allows the application of natural ventilation and daylighting. Reduction of 20% energy demand was achieved by these passive designs. To further lower the carbon emission on operation, energy-efficient air-conditioning (A/C) systems using desiccant dehumidification, underfloor air supply and radiant cooling have also contributed on achieving an ultralow energy use value. Amalgamated saving of these passive and active systems are over 45% when compared with the design per existing local building energy codes.

Description: State-of-the-art next-generation sequencing, transcriptomics, proteomics and other high-throughput ‘omics' technologies enable the efficient generation of large experimental data sets. These data may yield unprecedented knowledge about molecular pathways in cells and their role in disease. Dimension reduction approaches have been widely used in exploratory analysis of single omics data sets. This review will focus on dimension reduction approaches for simultaneous exploratory analyses of multiple data sets. These methods extract the linear relationships that best explain the correlated structure across data sets, the variability both within and between variables (or observations) and may highlight data issues such as batch effects or outliers. We explore dimension reduction techniques as one of the emerging approaches for data integration, and how these can be applied to increase our understanding of biological systems in normal physiological function and disease.

Description: Motivation: DNA methylation is an important epigenetic modification related to a variety of diseases including cancers. We focus on the methylation data from Illumina’s Infinium HumanMethylation450 BeadChip. One of the key issues of methylation analysis is to detect the differential methylation sites between case and control groups. Previous approaches describe data with simple summary statistics or kernel function, and then use statistical tests to determine the difference. However, a summary statistics-based approach cannot capture complicated underlying structure, and a kernel function-based approach lacks interpretability of results. Results: We propose a novel method D 3 M, for detection of differential distribution of methylation, based on distribution-valued data. Our method can detect the differences in high-order moments, such as shapes of underlying distributions in methylation profiles, based on the Wasserstein metric. We test the significance of the difference between case and control groups and provide an interpretable summary of the results. The simulation results show that the proposed method achieves promising accuracy and shows favorable results compared with previous methods. Glioblastoma multiforme and lower grade glioma data from The Cancer Genome Atlas show that our method supports recent biological advances and suggests new insights. Availability and Implementation: R implemented code is freely available from https://github.com/ymatts/D3M/ . Contact: ymatsui@med.nagoya-u.ac.jp or shimamura@med.nagoya-u.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Similarity-based methods have been widely used in order to infer the properties of genes and gene products containing little or no experimental annotation. New approaches that overcome the limitations of methods that rely solely upon sequence similarity are attracting increased attention. One of these novel approaches is to use the organization of the structural domains in proteins. Results: We propose a method for the automatic annotation of protein sequences in the UniProt Knowledgebase (UniProtKB) by comparing their domain architectures, classifying proteins based on the similarities and propagating functional annotation. The performance of this method was measured through a cross-validation analysis using the Gene Ontology (GO) annotation of a sub-set of UniProtKB/Swiss-Prot. The results demonstrate the effectiveness of this approach in detecting functional similarity with an average F-score: 0.85. We applied the method on nearly 55.3 million uncharacterized proteins in UniProtKB/TrEMBL resulted in 44 818 178 GO term predictions for 12 172 114 proteins. 22% of these predictions were for 2 812 016 previously non-annotated protein entries indicating the significance of the value added by this approach. Availability and implementation: The results of the method are available at: ftp://ftp.ebi.ac.uk/pub/contrib/martin/DAAC/ . Contact: tdogan@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Species identification and quantification are common tasks in metagenomics and pathogen detection studies. The most recent techniques are built on mapping the sequenced reads against a reference database (e.g. whole genomes, marker genes, proteins) followed by application-dependent analysis steps. Although these methods have been proven to be useful in many scenarios, there is still room for improvement in species and strain level detection, mainly for low abundant organisms. Results: We propose a new method: DUDes, a reference-based taxonomic profiler that introduces a novel top-down approach to analyze metagenomic Next-generation sequencing (NGS) samples. Rather than predicting an organism presence in the sample based only on relative abundances, DUDes first identifies possible candidates by comparing the strength of the read mapping in each node of the taxonomic tree in an iterative manner. Instead of using the lowest common ancestor we propose a new approach: the deepest uncommon descendent. We showed in experiments that DUDes works for single and multiple organisms and can identify low abundant taxonomic groups with high precision. Availability and Implementation: DUDes is open source and it is available at http://sf.net/p/dudes Supplementary information: Supplementary data are available at Bioinformatics online. Contact: renardB@rki.de

Description: Motivation: Moonlighting proteins (MPs) show multiple cellular functions within a single polypeptide chain. To understand the overall landscape of their functional diversity, it is important to establish a computational method that can identify MPs on a genome scale. Previously, we have systematically characterized MPs using functional and omics-scale information. In this work, we develop a computational prediction model for automatic identification of MPs using a diverse range of protein association information. Results: We incorporated a diverse range of protein association information to extract characteristic features of MPs, which range from gene ontology (GO), protein–protein interactions, gene expression, phylogenetic profiles, genetic interactions and network-based graph properties to protein structural properties, i.e. intrinsically disordered regions in the protein chain. Then, we used machine learning classifiers using the broad feature space for predicting MPs. Because many known MPs lack some proteomic features, we developed an imputation technique to fill such missing features. Results on the control dataset show that MPs can be predicted with over 98% accuracy when GO terms are available. Furthermore, using only the omics-based features the method can still identify MPs with over 75% accuracy. Last, we applied the method on three genomes: Saccharomyces cerevisiae , Caenorhabditis elegans and Homo sapiens , and found that about 2–10% of proteins in the genomes are potential MPs. Availability and Implementation: Code available at http://kiharalab.org/MPprediction Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Design of protein–protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5–15 amino acid long), are natural candidates for inhibition of protein–protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. Results: In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein–protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space ( 20n ) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. Availability and implementation: An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/. Contact: danielza@post.tau.ac.il ; wolfson@tau.ac.il

Description: Motivation: Whole-genome low-coverage sequencing has been combined with linkage-disequilibrium (LD)-based genotype refinement to accurately and cost-effectively infer genotypes in large cohorts of individuals. Most genotype refinement methods are based on hidden Markov models, which are accurate but computationally expensive. We introduce an algorithm that models LD using a simple multivariate Gaussian distribution. The key feature of our algorithm is its speed. Results: Our method is hundreds of times faster than other methods on the same data set and its scaling behaviour is linear in the number of samples. We demonstrate the performance of the method on both low- and high-coverage samples. Availability and implementation: The source code is available at https://github.com/illumina/marvin Contact: rarthur@illumina.com Supplementary information: Supplementary data are available at Bioinformatics online .

Description: Motivation : T-cell epitopes serve as molecular keys to initiate adaptive immune responses. Identification of T-cell epitopes is also a key step in rational vaccine design. Most available methods are driven by informatics and are critically dependent on experimentally obtained training data. Analysis of a training set from Immune Epitope Database (IEDB) for several alleles indicates that the sampling of the peptide space is extremely sparse covering a tiny fraction of the possible nonamer space, and also heavily skewed, thus restricting the range of epitope prediction. Results : We present a new epitope prediction method that has four distinct computational modules: (i) structural modelling, estimating statistical pair-potentials and constraint derivation, (ii) implicit modelling and interaction profiling, (iii) feature representation and binding affinity prediction and (iv) use of graphical models to extract peptide sequence signatures to predict epitopes for HLA class I alleles. Conclusions : HLaffy is a novel and efficient epitope prediction method that predicts epitopes for any Class-1 HLA allele, by estimating the binding strengths of peptide-HLA complexes which is achieved through learning pair-potentials important for peptide binding. It relies on the strength of the mechanistic understanding of peptide-HLA recognition and provides an estimate of the total ligand space for each allele. The performance of HLaffy is seen to be superior to the currently available methods. Availability and implementation : The method is made accessible through a webserver http://proline.biochem.iisc.ernet.in/HLaffy . Contact : nchandra@biochem.iisc.ernet.in Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: In vitro and in vivo cell proliferation is often studied using the dye carboxyfluorescein succinimidyl ester (CFSE). The CFSE time-series data provide information about the proliferation history of populations of cells. While the experimental procedures are well established and widely used, the analysis of CFSE time-series data is still challenging. Many available analysis tools do not account for cell age and employ optimization methods that are inefficient (or even unreliable). Results: We present a new model-based analysis method for CFSE time-series data. This method uses a flexible description of proliferating cell populations, namely, a division-, age- and label-structured population model. Efficient maximum likelihood and Bayesian estimation algorithms are introduced to infer the model parameters and their uncertainties. These methods exploit the forward sensitivity equations of the underlying partial differential equation model for efficient and accurate gradient calculation, thereby improving computational efficiency and reliability compared with alternative approaches and accelerating uncertainty analysis. The performance of the method is assessed by studying a dataset for immune cell proliferation. This revealed the importance of different factors on the proliferation rates of individual cells. Among others, the predominate effect of cell age on the division rate is found, which was not revealed by available computational methods. Availability and implementation: The MATLAB source code implementing the models and algorithms is available from http://janhasenauer.github.io/ShAPE-DALSP/ . Contact: jan.hasenauer@helmholtz-muenchen.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The challenges of successfully applying causal inference methods include: (i) satisfying underlying assumptions, (ii) limitations in data/models accommodated by the software and (iii) low power of common multiple testing approaches. Results: The causal inference test (CIT) is based on hypothesis testing rather than estimation, allowing the testable assumptions to be evaluated in the determination of statistical significance. A user-friendly software package provides P -values and optionally permutation-based FDR estimates ( q -values) for potential mediators. It can handle single and multiple binary and continuous instrumental variables, binary or continuous outcome variables and adjustment covariates. Also, the permutation-based FDR option provides a non-parametric implementation. Conclusion: Simulation studies demonstrate the validity of the cit package and show a substantial advantage of permutation-based FDR over other common multiple testing strategies. Availability and implementation: The cit open-source R package is freely available from the CRAN website ( https://cran.r-project.org/web/packages/cit/index.html ) with embedded C ++ code that utilizes the GNU Scientific Library, also freely available ( http://www.gnu.org/software/gsl/ ). Contact: joshua.millstein@usc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The vast majority of the many thousands of disease-associated single nucleotide polymorphisms (SNPs) lie in the non-coding part of the genome. They are likely to affect regulatory elements, such as enhancers and promoters, rather than the function of a protein. To understand the molecular mechanisms underlying genetic diseases, it is therefore increasingly important to study the effect of a SNP on nearby molecular traits such as chromatin or transcription factor binding. Results: We developed SNPhood , a user-friendly Bioconductor R package to investigate, quantify and visualise the local epigenetic neighbourhood of a set of SNPs in terms of chromatin marks or TF binding sites using data from NGS experiments. Availability and implementation: SNPhood is publicly available and maintained as an R Bioconductor package at http://bioconductor.org/packages/SNPhood/ . Contact: judith.zaugg@embl.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Versatile and efficient variant calling tools are needed to analyze large scale sequencing datasets. In particular, identification of copy number changes remains a challenging task due to their complexity, susceptibility to sequencing biases, variation in coverage data and dependence on genome-wide sample properties, such as tumor polyploidy or polyclonality in cancer samples. Results: We have developed a new tool, Canvas, for identification of copy number changes from diverse sequencing experiments including whole-genome matched tumor-normal and single-sample normal re-sequencing, as well as whole-exome matched and unmatched tumor-normal studies. In addition to variant calling, Canvas infers genome-wide parameters such as cancer ploidy, purity and heterogeneity. It provides fast and easy-to-run workflows that can scale to thousands of samples and can be easily incorporated into variant calling pipelines. Availability and Implementation: Canvas is distributed under an open source license and can be downloaded from https://github.com/Illumina/canvas . Contact: eroller@illumina.com Supplementary information: Supplementary data are available at Bioinformatics online.

Description: p ileup.js is a new browser-based genome viewer. It is designed to facilitate the investigation of evidence for genomic variants within larger web applications. It takes advantage of recent developments in the JavaScript ecosystem to provide a modular, reliable and easily embedded library. Availability and implementation: The code and documentation for pileup.js is publicly available at https://github.com/hammerlab/pileup.js under the Apache 2.0 license. Contact : correspondence@hammerlab.org

Description: Motivation: We present an update to the pathway enrichment analysis tool ‘Pathway Analysis by Randomization Incorporating Structure (PARIS)’ that determines aggregated association signals generated from genome-wide association study results. Pathway-based analyses highlight biological pathways associated with phenotypes. PARIS uses a unique permutation strategy to evaluate the genomic structure of interrogated pathways, through permutation testing of genomic features, thus eliminating many of the over-testing concerns arising with other pathway analysis approaches. Results: We have updated PARIS to incorporate expanded pathway definitions through the incorporation of new expert knowledge from multiple database sources, through customized user provided pathways, and other improvements in user flexibility and functionality. Availability and implementation: PARIS is freely available to all users at https://ritchielab.psu.edu/software/paris-download . Contact: jnc43@case.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Nucleotide Similarity Scanner (NSimScan) is specialized for searching massive DNA databases for distant similarities. Its targeted applications include phylogenomics, comparative and functional studies of non-coding sequences, contamination detection, etc. NSimScan outperforms industry standard tools in combined sensitivity, accuracy and speed, operating at sensitivity similar to BLAST, accuracy of ssearch and speed of MegaBLAST. Availability and implementation: NSimScan is available at https://github.com/abadona/qsimscan as a part of QSimScan package. It is implemented in C ++, distributed under MIT license and supported on Linux, OS X and Windows (with cygwin). Contact: dkaznadzey@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : We present TreeDom, a web tool for graphically analysing the evolutionary history of domains in multi-domain proteins. Individual domains on the same protein chain may have distinct evolutionary histories, which is important to grasp in order to understand protein function. For instance, it may be important to know whether a domain was duplicated recently or long ago, to know the origin of inserted domains, or to know the pattern of domain loss within a protein family. TreeDom uses the Pfam database as the source of domain annotations, and displays these on a sequence tree. An advantage of TreeDom is that the user can limit the analysis to N sequences that are most similar to a query, or provide a list of sequence IDs to include. Using the Pfam alignment of the selected sequences, a tree is built and displayed together with the domain architecture of each sequence. Availablility and implementation: http://TreeDom.sbc.su.se Contact: Erik.Sonnhammer@scilifelab.se

Description: : The NCI-60 human tumor cell line panel is an invaluable resource for cancer researchers, providing drug sensitivity, molecular and phenotypic data for a range of cancer types. CellMiner is a web resource that provides tools for the acquisition and analysis of quality-controlled NCI-60 data. CellMiner supports queries of up to 150 drugs or genes, but the output is an Excel file for each drug or gene. This output format makes it difficult for researchers to explore the data from large queries. CellMiner Companion is a web application that facilitates the exploration and visualization of output from CellMiner, further increasing the accessibility of NCI-60 data. Availability and Implementation: The web application is freely accessible at https://pul-bioinformatics.shinyapps.io/CellMinerCompanion . The R source code can be downloaded at https://github.com/pepascuzzi/CellMinerCompanion.git . Contact: ppascuzz@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation and optimization of advanced analysis methods for live cell single molecule microscopy data. Availability and implementation: SMeagol runs on Matlab R2014 and later, and uses compiled binaries in C for reaction–diffusion simulations. Documentation, source code and binaries for Mac OS, Windows and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net . Contact: johan.elf@icm.uu.se Supplementary information : Supplementary data are available at Bioinformatics online.

Description: The ciphertext retrieval is of paramount importance for data confidentiality and utilization in mobile cloud environment. The receiver, usually equipped with resource constrained devices, retrieves data stored in the cloud server by submitting a confidential request (or trapdoor) to the cloud. Previous schemes need at least one exponentiation operation in group $\mathbb {G}$ for each keyword to generate the trapdoor, which is quite burdensome for mobile devices to support such computational cost. The computational cost of trapdoor generation limits the application of ciphertext retrieval, especially in a wireless environment. In this paper, we propose the first online/offline ciphertext retrieval (OOCR) scheme, where the trapdoor generation is split into two phases: offline phase and online phase . Most of the computation of the trapdoor could be performed in the offline phase prior to knowing the keyword. The generation of the real trapdoor with keyword can be done efficiently in the online phase. The most challenging task is to resist the so-called insider attacks, which is about keyword guessing attacks from the untrusted cloud server. We also build a novel framework to resist insider attacks and propose an OOCR scheme against insider attacks. Our semantic security proof and performance analysis demonstrate that the proposal is practical for mobile cloud applications.

Description: In this paper, we point out some faulty instantiations of threshold ring signatures (TRS) based on the threshold proof-of-knowledge (TPoK) protocol. Although a TRS can be regarded as the non-interactive version of the TPoK, the computational domains of the variables should be carefully chosen. We show that by choosing some inappropriate domains, two such instantiations suffer from forgery and anonymity attacks. Our attacks rely on algebraic techniques which involve solving some particular instances of the well-known subset sum problem. While we focus our attacks on two particular instantiations of the TRS, they are generic and are applicable to other schemes with the same choice of domains or a similar structure. We believe this paper can act as an important security remark on the design of future TRS schemes.

Description: The typical Secure Document Management System (SDMS) uses cryptography or access control mechanisms to restrict illegal access by unauthorized users to digital documents. However, these techniques are insufficient when authorized users betray the trust of their organizations, distributing sensitive digital documents to unauthorized users. This paper presents a novel end-to-end approach to construct a robust SDMS able to guarantee not only the integrity and confidentiality of digital documents (data-centric security), but also providing robust insider threat tracing mechanisms (user-centric security). As far as the authors' knowledge extends, this is the first contribution that analyses security issues of SDMS considering data-centric (by means of encryption) and user-centric (based on fingerprinting) security services for the construction of an SDMS. Security requirements are identified from the modeling of a digital document's lifecycle. Then cryptographic techniques are carefully coupled with a fingerprinting technique at specific stages of the proposed document lifecycle. As a proof of concept, an SDMS was created, implemented and evaluated, demonstrating its feasibility for deployment in production environments. The robustness of the SDMS was proved, using standard cryptographic algorithms and secure key lengths. The created SDMS also resisted the collusion and retyping attacks commonly directed at fingerprinting applications.

Description: Nowadays, trust systems (TSs) are widely used for tackling dishonest entities in many modern environments. However, these systems are vulnerable to some kinds of attacks where attackers try to deceive the system using sequences of misleading behaviors and dishonest recommendations. A robust TS is expected to function properly even in the possibility of such attacks. To the best of our knowledge, simulation has been the main approach for evaluation of TSs so far, and there is no remarkable verification method for this aim. In this paper, a method for quantitative verification of TSs' robustness against malicious attackers is proposed. The proposed method consists of a formalism for specifying any given trust model named TS attack process that is cast into partially observable Markov decision process mathematical framework. The proposed method is capable of verifying TSs against both well-known attacks and the worst possible attack scenario. The method could also be used to help adjusting parameters of the given TS. Moreover, a quantitative robustness measure is introduced, which helps to compare the robustness of different TSs. To illustrate the applicability of the proposed method, a number of case studies for analysis and comparison of selected trust models (including Subjective Logic and REGRET) are presented.

Description: Multivariate cryptographic systems are one of the most popular public key cryptographic systems, since they have the potential to resist quantum computer attacks. Multivariate signatures have few applications where low area is more of a priority since they are much larger than rivest-shamir-adleman and elliptic curves cryptography. In this paper, we propose a very small cryptographic processor for multivariate signatures and enhance our design in three directions. First, we propose a Modular Arithmetic Logic Unit based on composite field representations. Second, we design a small instruction set. Third, we adapt register reuse and time sharing. Via further other minor optimizations and by integrating the major improvement above, our design is implemented on a small Xilinx field programmable logic array and utilizes only 47 flip flops, 155 look up tables and 92 slices. Its small area would present a significant saving, including fitting into a smaller device, e.g. radio frequency identification tag. Our design can generate multivariate signatures with a moderate speed, e.g. Unbalanced Oil–Vinegar Signature, Rainbow and extensions of Tame Transformation Signature, which is sufficient for numerous applications where area usage is more of a priority. Comparison results show that our design is 50% smaller than the smallest available public key cryptographic system.

Description: Inversions in small finite fields are playing a key role in many areas. We present techniques to exploit binary trees for fast inversions in $GF(2^n)$ and $GF(p)$ , where $n$ is a positive integer and $p$ is a prime number. The non-pipelined versions of our design in $GF(2^n)$ and $GF(p)$ have the execution time of $(n-1)(T_{AND}+T_{XOR})$ and $\lfloor \log _2p\rfloor (T_{AND}+T_{XOR})$ , where $T_{AND}$ and ${T_{XOR}}$ are delays of AND and XOR gates, respectively. The pipelined version of our design has a throughput rate of one result per $T_{AND}$ (or $T_{XOR}$ ). The latency is the greater value between $T_{AND}$ and $T_{XOR}$ . In other words, the time complexities of non-pipelined and pipelined versions are $O(n)$ (or $O(log_2p)$ ) and $O(1)$ , respectively. Experimental results and comparisons show that our design provides significant reductions in both the execution time and time–area product, e.g. the execution time of inversion in $GF(2^{12})$ is reduced by 73 $\%$ and time–area product of inversion in $GF(2^6)$ is reduced by 77 $\%$ .

Description: Motivation : Photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP) is an experimental method based on next-generation sequencing for identifying the RNA interaction sites of a given protein. The method deliberately inserts T-to-C substitutions at the RNA-protein interaction sites, which provides a second layer of evidence compared with other CLIP methods. However, the experiment includes several sources of noise which cause both low-frequency errors and spurious high-frequency alterations. Therefore, rigorous statistical analysis is required in order to separate true T-to-C base changes, following cross-linking, from noise. So far, most of the existing PAR-CLIP data analysis methods focus on discarding the low-frequency errors and rely on high-frequency substitutions to report binding sites, not taking into account the possibility of high-frequency false positive substitutions. Results : Here, we introduce BMix , a new probabilistic method which explicitly accounts for the sources of noise in PAR-CLIP data and distinguishes cross-link induced T-to-C substitutions from low and high-frequency erroneous alterations. We demonstrate the superior speed and accuracy of our method compared with existing approaches on both simulated and real, publicly available human datasets. Availability and implementation : The model is freely accessible within the BMix toolbox at www.cbg.bsse.ethz.ch/software/BMix , available for Matlab and R. Supplementary information: Supplementary data is available at Bioinformatics online. Contact : niko.beerenwinkel@bsse.ethz.ch

Description: Motivation: Gene networks have become a central tool in the analysis of genomic data but are widely regarded as hard to interpret. This has motivated a great deal of comparative evaluation and research into best practices. We explore the possibility that this may lead to overfitting in the field as a whole. Results: We construct a model of ‘research communities’ sampling from real gene network data and machine learning methods to characterize performance trends. Our analysis reveals an important principle limiting the value of replication, namely that targeting it directly causes ‘easy’ or uninformative replication to dominate analyses. We find that when sampling across network data and algorithms with similar variability, the relationship between replicability and accuracy is positive (Spearman’s correlation, r s ~0.33) but where no such constraint is imposed, the relationship becomes negative for a given gene function ( r s ~ –0.13). We predict factors driving replicability in some prior analyses of gene networks and show that they are unconnected with the correctness of the original result, instead reflecting replicable biases. Without these biases, the original results also vanish replicably. We show these effects can occur quite far upstream in network data and that there is a strong tendency within protein–protein interaction data for highly replicable interactions to be associated with poor quality control. Availability and implementation: Algorithms, network data and a guide to the code available at: https://github.com/wimverleyen/AggregateGeneFunctionPrediction . Contact: jgillis@cshl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Recent advances in single molecule real-time (SMRT) and nanopore sequencing technologies have enabled high-quality assemblies from long and inaccurate reads. However, these approaches require high coverage by long reads and remain expensive. On the other hand, the inexpensive short reads technologies produce accurate but fragmented assemblies. Thus, a hybrid approach that assembles long reads (with low coverage) and short reads has a potential to generate high-quality assemblies at reduced cost. Results: We describe hybrid SPA des algorithm for assembling short and long reads and benchmark it on a variety of bacterial assembly projects. Our results demonstrate that hybrid SPA des generates accurate assemblies (even in projects with relatively low coverage by long reads) thus reducing the overall cost of genome sequencing. We further present the first complete assembly of a genome from single cells using SMRT reads. Availability and implementation: hybrid SPA des is implemented in C++ as a part of SPAdes genome assembler and is publicly available at http://bioinf.spbau.ru/en/spades Contact: d.antipov@spbu.ru Supplementary information: supplementary data are available at Bioinformatics online.

Description: Motivation: There are numerous examples of RNA–RNA complexes, including microRNA–mRNA and small RNA–mRNA duplexes for regulation of translation, guide RNA interactions with target RNA for post-transcriptional modification and small nuclear RNA duplexes for splicing. Predicting the base pairs formed between two interacting sequences remains difficult, at least in part because of the competition between unimolecular and bimolecular structure. Results: Two algorithms were developed for improved prediction of bimolecular RNA structure that consider the competition between self-structure and bimolecular structure. These algorithms utilize two novel approaches to evaluate accessibility: free energy density minimization and pseudo-energy minimization. Free energy density minimization minimizes the folding free energy change per nucleotide involved in an intermolecular secondary structure. Pseudo-energy minimization (called AccessFold) minimizes the sum of free energy change and a pseudo-free energy penalty for bimolecular pairing of nucleotides that are unlikely to be accessible for bimolecular structure. The pseudo-free energy, derived from unimolecular pairing probabilities, is applied per nucleotide in bimolecular pairs, and this approach is able to predict binding sites that are split by unimolecular structures. A benchmark set of 17 bimolecular RNA structures was assembled to assess structure prediction. Pseudo-energy minimization provides a statistically significant improvement in sensitivity over the method that was found in a benchmark to be the most accurate previously available method, with an improvement from 36.8% to 57.8% in mean sensitivity for base pair prediction. Availability and implementation: Pseudo-energy minimization is available for download as AccessFold, under an open-source license and as part of the RNAstructure package, at: http://rna.urmc.rochester.edu/RNAstructure.html . Contact: david_mathews@urmc.rochester.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Simulating complex evolution scenarios of multiple populations is an important task for answering many basic questions relating to population genomics. Apart from the population samples, the underlying Ancestral Recombinations Graph (ARG) is an additional important means in hypothesis checking and reconstruction studies. Furthermore, complex simulations require a plethora of interdependent parameters making even the scenario-specification highly non-trivial. Results: We present an algorithm SimRA that simulates generic multiple population evolution model with admixture. It is based on random graphs that improve dramatically in time and space requirements of the classical algorithm of single populations. Using the underlying random graphs model, we also derive closed forms of expected values of the ARG characteristics i.e., height of the graph, number of recombinations, number of mutations and population diversity in terms of its defining parameters. This is crucial in aiding the user to specify meaningful parameters for the complex scenario simulations, not through trial-and-error based on raw compute power but intelligent parameter estimation. To the best of our knowledge this is the first time closed form expressions have been computed for the ARG properties. We show that the expected values closely match the empirical values through simulations. Finally, we demonstrate that SimRA produces the ARG in compact forms without compromising any accuracy. We demonstrate the compactness and accuracy through extensive experiments. Availability and implementation : SimRA ( Sim ulation based on R andom graph A lgorithms) source, executable, user manual and sample input-output sets are available for downloading at: https://github.com/ComputationalGenomics/SimRA Contact : parida@us.ibm.com Supplementary information: Supplementary data are available at Bioinformatics online.