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    ADAGE signature analysis: differential expression analysis with data-defined gene sets.
    BMC Bioinformatics 2017 Nov 22;18(1):512. Epub 2017 Nov 22.
    Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
    Background: Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Read More

    Unsupervised gene selection using biological knowledge : application in sample clustering.
    BMC Bioinformatics 2017 Nov 22;18(1):513. Epub 2017 Nov 22.
    IIT Ropar, Department of Computer Science and engineering, Punjab, India.
    Background: Classification of biological samples of gene expression data is a basic building block in solving several problems in the field of bioinformatics like cancer and other disease diagnosis and making a proper treatment plan. One big challenge in sample classification is handling large dimensional and redundant gene expression data. To reduce the complexity of handling this high dimensional data, gene/feature selection plays a major role. Read More

    RNA methylation and diseases: experimental results, databases, Web servers and computational models.
    Brief Bioinform 2017 Nov 18. Epub 2017 Nov 18.
    Ribonucleic acid (RNA) methylation is a type of posttranscriptional modifications occurring in all kingdoms of life. It is strongly related to important biological process, thus making it linked to a number of human diseases. Owing to the development of high-throughput sequencing technology, plenty of achievement had been obtained in RNA methylation research recently. Read More

    Synima: a Synteny imaging tool for annotated genome assemblies.
    BMC Bioinformatics 2017 Nov 21;18(1):507. Epub 2017 Nov 21.
    Department of Infectious Disease Epidemiology, Imperial College London, London, W2 1PG, UK.
    Background: Ortholog prediction and synteny visualization across whole genomes are valuable methods for detecting and representing a range of evolutionary processes such as genome expansion, chromosomal rearrangement, and chromosomal translocation. Few standalone methods are currently available to visualize synteny across any number of annotated genomes.

    Results: Here, I present a Synteny Imaging tool (Synima) written in Perl, which uses the graphical features of R. Read More

    Norgal: extraction and de novo assembly of mitochondrial DNA from whole-genome sequencing data.
    BMC Bioinformatics 2017 Nov 21;18(1):510. Epub 2017 Nov 21.
    Department of Bio and Health Informatics, Technical University of Denmark, Kemitorvet, Building 208, Kgs Lyngby, 2800, Denmark.
    Background: Whole-genome sequencing (WGS) projects provide short read nucleotide sequences from nuclear and possibly organelle DNA depending on the source of origin. Mitochondrial DNA is present in animals and fungi, while plants contain DNA from both mitochondria and chloroplasts. Current techniques for separating organelle reads from nuclear reads in WGS data require full reference or partial seed sequences for assembling. Read More

    Fast batch searching for protein homology based on compression and clustering.
    BMC Bioinformatics 2017 Nov 21;18(1):508. Epub 2017 Nov 21.
    College of Computer Science and Technology, Dalian University of Technology, No.2, Linggong Road, Dalian, China.
    Background: In bioinformatics community, many tasks associate with matching a set of protein query sequences in large sequence datasets. To conduct multiple queries in the database, a common used method is to run BLAST on each original querey or on the concatenated queries. It is inefficient since it doesn't exploit the common subsequences shared by queries. Read More

    Brain medical image diagnosis based on corners with importance-values.
    BMC Bioinformatics 2017 Nov 21;18(1):505. Epub 2017 Nov 21.
    Research center for intelligent information processing, College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China.
    Background: Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. Read More

    Integration of RNA-Seq data with heterogeneous microarray data for breast cancer profiling.
    BMC Bioinformatics 2017 Nov 21;18(1):506. Epub 2017 Nov 21.
    Department of Computer Architecture and Technology, University of Granada, Periodista Rafael Gómez Montero, 2, Granada, 18014, Spain.
    Background: Nowadays, many public repositories containing large microarray gene expression datasets are available. However, the problem lies in the fact that microarray technology are less powerful and accurate than more recent Next Generation Sequencing technologies, such as RNA-Seq. In any case, information from microarrays is truthful and robust, thus it can be exploited through the integration of microarray data with RNA-Seq data. Read More

    Swellix: a computational tool to explore RNA conformational space.
    BMC Bioinformatics 2017 Nov 21;18(1):504. Epub 2017 Nov 21.
    , 101 Stephenson Parkway, Norman, OK, 73019, USA.
    Background: The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to compute all possible non-pseudoknotted RNA structures for RNA sequences. The Swellix program builds on the Crumple program and can include experimental constraints on global RNA structures such as the minimum number and lengths of helices from crystallography, cryoelectron microscopy, or in vivo crosslinking and chemical probing methods. Read More

    Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks.
    Bioinformatics 2017 Nov 16. Epub 2017 Nov 16.
    Department of Informatics, Technical University of Munich, Boltzmannstraße, 85748 Garching, Germany.
    Motivation: Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries, or polyadenylation site. Deep learning has become the approach of choice for modeling regulatory sequences because of its strength to learn complex sequence features. However, modeling relative distances to genomic landmarks in deep neural networks has not been addressed. Read More

    bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests.
    BMC Bioinformatics 2017 Nov 18;18(1):503. Epub 2017 Nov 18.
    Department of Statistical Sciences, University of Padova, via C. Battisti, 241, Padova, 35121, Italy.
    Background: Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). Read More

    GPU-based detection of protein cavities using Gaussian surfaces.
    BMC Bioinformatics 2017 Nov 16;18(1):493. Epub 2017 Nov 16.
    Universidade da Beira Interior, Av. Marques D'Ávila e Bolama, Covilhã, 6200-001, Portugal.
    Background: Protein cavities play a key role in biomolecular recognition and function, particularly in protein-ligand interactions, as usual in drug discovery and design. Grid-based cavity detection methods aim at finding cavities as aggregates of grid nodes outside the molecule, under the condition that such cavities are bracketed by nodes on the molecule surface along a set of directions (not necessarily aligned with coordinate axes). Therefore, these methods are sensitive to scanning directions, a problem that we call cavity ground-and-walls ambiguity, i. Read More

    dbMDEGA: a database for meta-analysis of differentially expressed genes in autism spectrum disorder.
    BMC Bioinformatics 2017 Nov 16;18(1):494. Epub 2017 Nov 16.
    Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, BaYi Road 461, Nanchang, 330006, China.
    Background: Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Read More

    ANAT 2.0: reconstructing functional protein subnetworks.
    BMC Bioinformatics 2017 Nov 16;18(1):495. Epub 2017 Nov 16.
    School of Computer Science, Tel Aviv University, 69978, Tel Aviv, Israel.
    Background: ANAT is a graphical, Cytoscape-based tool for the inference of protein networks that underlie a process of interest. The ANAT tool allows the user to perform network reconstruction under several scenarios in a number of organisms including yeast and human.

    Results: Here we report on a new version of the tool, ANAT 2. Read More

    TRAVeLer: a tool for template-based RNA secondary structure visualization.
    BMC Bioinformatics 2017 Nov 15;18(1):487. Epub 2017 Nov 15.
    Faculty of Mathematics and Physics, Charles University, Prague, 11800, Czech Republic.
    Background: Visualization of RNA secondary structures is a complex task, and, especially in the case of large RNA structures where the expected layout is largely habitual, the existing visualization tools often fail to produce suitable visualizations. This led us to the idea to use existing layouts as templates for the visualization of new RNAs similarly to how templates are used in homology-based structure prediction.

    Results: This article introduces Traveler, a software tool enabling visualization of a target RNA secondary structure using an existing layout of a sufficiently similar RNA structure as a template. Read More

    Reconstructing cancer karyotypes from short read data: the half empty and half full glass.
    BMC Bioinformatics 2017 Nov 15;18(1):488. Epub 2017 Nov 15.
    Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv-Yafo, Israel.
    Background: During cancer progression genomes undergo point mutations as well as larger segmental changes. The latter include, among others, segmental deletions duplications, translocations and inversions.The result is a highly complex, patient-specific cancer karyotype. Read More

    SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome.
    BMC Bioinformatics 2017 Nov 15;18(1):485. Epub 2017 Nov 15.
    Department of Computer Science, The University of Western Ontario, London, N6A 5B7, Ontario, Canada.
    Background: Proteins perform their functions usually by interacting with other proteins. Predicting which proteins interact is a fundamental problem. Experimental methods are slow, expensive, and have a high rate of error. Read More

    Usability of human Infinium MethylationEPIC BeadChip for mouse DNA methylation studies.
    BMC Bioinformatics 2017 Nov 15;18(1):486. Epub 2017 Nov 15.
    Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
    Background: The advent of array-based genome-wide DNA methylation methods has enabled quantitative measurement of single CpG methylation status at relatively low cost and sample input. Whereas the use of Infinium Human Methylation BeadChips has shown great utility in clinical studies, no equivalent tool is available for rodent animal samples. We examined the feasibility of using the new Infinium MethylationEPIC BeadChip for studying DNA methylation in mouse. Read More

    ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.
    BMC Bioinformatics 2017 Nov 14;18(1):480. Epub 2017 Nov 14.
    Electrical Engineering and Computer Science Department, University of Missouri, Columbia, MO, 65211, USA.
    Background: With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e. Read More

    Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs.
    BMC Bioinformatics 2017 Nov 14;18(1):479. Epub 2017 Nov 14.
    Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
    Background: MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Read More

    GFF3sort: a novel tool to sort GFF3 files for tabix indexing.
    BMC Bioinformatics 2017 Nov 14;18(1):482. Epub 2017 Nov 14.
    Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
    Background: The traditional method of visualizing gene annotation data in JBrowse is converting GFF3 files to JSON format, which is time-consuming. The latest version of JBrowse supports rendering sorted GFF3 files indexed by tabix, a novel strategy that is more convenient than the original conversion process. However, current tools available for GFF3 file sorting have some limitations and their sorting results would lead to erroneous rendering in JBrowse. Read More

    Analysis of breast cancer subtypes by AP-ISA biclustering.
    BMC Bioinformatics 2017 Nov 14;18(1):481. Epub 2017 Nov 14.
    State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Clinical Research Center for Oral Diseases, Department of Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.
    Background: Gene expression profiling has led to the definition of breast cancer molecular subtypes: Basal-like, HER2-enriched, LuminalA, LuminalB and Normal-like. Different subtypes exhibit diverse responses to treatment. In the past years, several traditional clustering algorithms have been applied to analyze gene expression profiling. Read More

    Identification of Topological Features in Renal Tumor Microenvironment Associated with Patient Survival.
    Bioinformatics 2017 Nov 9. Epub 2017 Nov 9.
    Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio 43210, USA.
    Motivation: As a highly heterogeneous disease, the progression of tumor is not only achieved by unlimited growth of the tumor cells, but also supported, stimulated, and nurtured by the microenvironment around it. However traditional qualitative and/or semi-quantitative parameters obtained by pathologist's visual examination have very limited capability to capture this interaction between tumor and its microenvironment. With the advent of digital pathology, computerized image analysis may provide a better tumor characterization and give new insights into this problem. Read More

    Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction.
    Bioinformatics 2017 Nov 9. Epub 2017 Nov 9.
    Department of Statiscts, University of Oxford, Oxford, OX1 3LB, United Kingdom.
    Motivation: Most current de novo structure prediction methods randomly sample protein conformations and thus require large amounts of computational resource. Here, we consider a sequential sampling strategy, building on ideas from recent experimental work which shows that many proteins fold cotranslationally.

    Results: We have investigated whether a pseudo-greedy search approach, which begins sequentially from one of the termini, can improve the performance and accuracy of de novo protein structure prediction. Read More

    microRPM: A microRNA Prediction Model based only on plant small RNA sequencing data.
    Bioinformatics 2017 Nov 9. Epub 2017 Nov 9.
    College of Biosciences and Biotechnology, Institute of Tropical Plant Sciences, National Cheng Kung University, Tainan 70101, Taiwan.
    Motivation: MicroRNAs (miRNAs) are endogenous non-coding small RNAs (of about 22 nucleotides), which play an important role in the post-transcriptional regulation of gene expression via either mRNA cleavage or translation inhibition. Several machine learning-based approaches have been developed to identify novel miRNAs from next generation sequencing (NGS) data. Typically, precursor/genomic sequences are required as references for most methods. Read More

    Predicting loop conformational ensembles.
    Bioinformatics 2017 Nov 10. Epub 2017 Nov 10.
    Department of Statistics, University of Oxford, Oxford, OX1 3LB, United Kingdom.
    Motivation: Protein function is often facilitated by the existence of multiple stable conformations. Structure prediction algorithms need to be able to model these different conformations accurately, and produce an ensemble of structures that represent a target's conformational diversity rather than just a single state. Here, we investigate whether current loop prediction algorithms are capable of this. Read More

    BugMat and FindNeighbour: command line and server applications for investigating bacterial relatedness.
    BMC Bioinformatics 2017 Nov 13;18(1):477. Epub 2017 Nov 13.
    Nuffield Department of Medicine, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK.
    Background: Large scale bacterial sequencing has made the determination of genetic relationships within large sequence collections of bacterial genomes derived from the same microbial species an increasingly common task. Solutions to the problem have application to public health (for example, in the detection of possible disease transmission), and as part of divide-and-conquer strategies selecting groups of similar isolates for computationally intensive methods of phylogenetic inference using (for example) maximal likelihood methods. However, the generation and maintenance of distance matrices is computationally intensive, and rapid methods of doing so are needed to allow translation of microbial genomics into public health actions. Read More

    A fragment based method for modeling of protein segments into cryo-EM density maps.
    BMC Bioinformatics 2017 Nov 13;18(1):475. Epub 2017 Nov 13.
    Institute of Medical Physics and Biophysics, University Medicine Berlin, Charitéplatz 1, 10117, Berlin, Germany.
    Background: Single-particle analysis of electron cryo-microscopy (cryo-EM) is a key technology for elucidation of macromolecular structures. Recent technical advances in hardware and software developments significantly enhanced the resolution of cryo-EM density maps and broadened the applicability and the circle of users. To facilitate modeling of macromolecules into cryo-EM density maps, fast and easy to use methods for modeling are now demanded. Read More

    Reference-guided de novo assembly approach improves genome reconstruction for related species.
    BMC Bioinformatics 2017 Nov 10;18(1):474. Epub 2017 Nov 10.
    Department of Evolutionary Biology and Environmental Studies (IEU), University of Zurich, Zurich, Switzerland.
    Background: The development of next-generation sequencing has made it possible to sequence whole genomes at a relatively low cost. However, de novo genome assemblies remain challenging due to short read length, missing data, repetitive regions, polymorphisms and sequencing errors. As more and more genomes are sequenced, reference-guided assembly approaches can be used to assist the assembly process. Read More

    Membranome 2.0: database for proteome-wide profiling of bitopic proteins and their dimers.
    Bioinformatics 2017 Nov 6. Epub 2017 Nov 6.
    Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, 428 Church St, Ann Arbor MI 48109-1065.
    Motivation: Structural studies of TM domains of single-spanning (bitopic) membrane proteins are impeded by their instability, flexibility, and heterogeneity. The new computational method TMDOCK allows reliable modeling of homodimers of transmembrane (TM) α-helices on a proteomic scale.

    Results: 3D models of 2,129 parallel homodimers formed by TM α-helices of bitopic proteins from six evolutionarily distant organisms were modeled by TMDOCK, verified through experimental data available for nearly 600 proteins, and included in the Membranome database (v. Read More

    Deep Learning for Tumor Classification in Imaging Mass Spectrometry.
    Bioinformatics 2017 Nov 8. Epub 2017 Nov 8.
    Center for Industrial Mathematics, University of Bremen, 28359 Bremen, Germany.
    Motivation: Tumor classification using Imaging Mass Spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to fully process the data. Since mass spectra exhibit certain structural similarities to image data, deep learning may offer a promising strategy for classification of IMS data as it has been successfully applied to image classification. Read More

    Bringing numerous methods for expression and promoter analysis to a public cloud computing service.
    Bioinformatics 2017 Nov 6. Epub 2017 Nov 6.
    Department of Statistics, University of Warwick, Coventry, CV4 7AL, UK.
    Summary: Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project. Read More

    A survey of software tools for microRNA discovery and characterization using RNA-seq.
    Brief Bioinform 2017 Nov 6. Epub 2017 Nov 6.
    Since the small RNA-sequencing (sRNA-seq) technology became available, it allowed the discovery of thousands new microRNAs (miRNAs) in humans and many other species, providing new data on these small RNAs (sRNAs) of high biological and translational relevance. MiRNA discovery has not yet reached saturation, even in the most studied model organisms, and many researchers are using sRNA-seq in studies with different aims in biomedicine, fundamental research and in applied animal sciences. We review several miRNA discovery and characterization software tools that implement different strategies, providing a useful guide for researchers to select the programs best suiting their study objectives and data. Read More

    LIBRA-WA: a web application for ligand binding site detection and protein function recognition.
    Bioinformatics 2017 Nov 6. Epub 2017 Nov 6.
    Department of Sciences, University of Roma Tre, 00146 Rome, Italy.
    Summary: Recently, LIBRA, a tool for active/ligand binding site prediction, was described. LIBRA's effectiveness was comparable to similar state-of-the-art tools; however, its scoring scheme, output presentation, dependence on local resources and overall convenience were amenable to improvements. To solve these issues, LIBRA-WA, a web application based on an improved LIBRA engine, has been developed, featuring a novel scoring scheme consistently improving LIBRA's performance, and a refined algorithm that can identify binding sites hosted at the interface between different subunits. Read More

    Complex analyses of inverted repeats in mitochondrial genomes revealed their importance and variability.
    Bioinformatics 2017 Nov 8. Epub 2017 Nov 8.
    The Czech Academy of Sciences, Institute of Biophysics, Královopolská 135, 612 65 Brno, Czech Republic.
    Motivation: The NCBI database contains mitochondrial DNA (mtDNA) genomes from numerous species. We investigated the presence and locations of inverted repeat sequences (IRs) in these mtDNA sequences, which are known to be important for regulating nuclear genomes.

    Results: IRs were identified in mtDNA in all species. Read More

    RepLong - de novo repeat identification using long read sequencing data.
    Bioinformatics 2017 Nov 6. Epub 2017 Nov 6.
    College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China.
    Motivation: The identification of repetitive elements is important in genome assembly and phylogenetic analyses. The existing de novo repeat identification methods exploiting the use of short reads are impotent in identifying long repeats. Since long reads are more likely to cover repeat regions completely, using long reads is more favorable for recognizing long repeats. Read More

    Cost-effective and accurate method of measuring fetal fraction using SNP imputation.
    Bioinformatics 2017 Nov 8. Epub 2017 Nov 8.
    GenomeCare, Suwon, Korea.
    Motivation: With the discovery of cell-free fetal DNA in maternal blood, the demand for non-invasive prenatal testing (NIPT) has been increasing. To obtain reliable NIPT results, it is important to accurately estimate the fetal fraction. In this study, we propose an accurate and cost-effective method for measuring fetal fractions using single-nucleotide polymorphisms (SNPs). Read More

    AIRVF: a filtering toolbox for precise variant calling in Ion Torrent sequencing.
    Bioinformatics 2017 Nov 6. Epub 2017 Nov 6.
    Severance Biomedical Science Institute.
    Summary: Ion Torrent sequencing is one of the most frequently used platforms in healthcare research and industry. Despite many advantages, platform-specific artifacts complicate efficient separation of true variants from errors, especially in variants with lower allele frequencies (<15%). Here, we developed a multi-step filtering toolbox AIRVF that works on flowgram, raw and mapped reads and called variants to reduce artifact-driven false variant calls. Read More

    PREFMD: a web server for protein structure refinement via molecular dynamics simulations.
    Bioinformatics 2017 Nov 8. Epub 2017 Nov 8.
    Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
    Summary: Refinement of protein structure models is a long-standing problem in structural bioinformatics. Molecular dynamics-based methods have emerged as an avenue to achieve consistent refinement. The PREFMD web server implements an optimized protocol based on the method successfully tested in CASP11. Read More

    Sequence-based information-theoretic features for gene essentiality prediction.
    BMC Bioinformatics 2017 Nov 9;18(1):473. Epub 2017 Nov 9.
    Transmission Systems Group, Jacobs University Bremen, Campus Ring 1, Bremen, D-28759, Germany.
    Background: Identification of essential genes is not only useful for our understanding of the minimal gene set required for cellular life but also aids the identification of novel drug targets in pathogens. In this work, we present a simple and effective gene essentiality prediction method using information-theoretic features that are derived exclusively from the gene sequences.

    Results: We developed a Random Forest classifier and performed an extensive model performance evaluation among and within 15 selected bacteria. Read More

    Privacy-preserving techniques of genomic data-a survey.
    Brief Bioinform 2017 Nov 7. Epub 2017 Nov 7.
    Genomic data hold salient information about the characteristics of a living organism. Throughout the past decade, pinnacle developments have given us more accurate and inexpensive methods to retrieve genome sequences of humans. However, with the advancement of genomic research, there is a growing privacy concern regarding the collection, storage and analysis of such sensitive human data. Read More

    MOAT: Efficient Detection of Highly Mutated Regions with the Mutations Overburdening Annotations Tool.
    Bioinformatics 2017 Nov 7. Epub 2017 Nov 7.
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA.
    Summary: Identifying genomic regions with higher than expected mutation count is useful for cancer driver detection. Previous parametric approaches require numerous cell-type-matched covariates for accurate background mutation-rate (BMR) estimation, which is not practical for many situations. Nonparametric, permutation-based approaches avoid this issue but usually suffer from considerable compute-time cost. Read More

    PERF: An Exhaustive Algorithm for Ultra-Fast and Efficient Identification of Microsatellites from Large DNA Sequences.
    Bioinformatics 2017 Nov 7. Epub 2017 Nov 7.
    CSIR - Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad - 500007, Telangana, India.
    Motivation: Microsatellites or Simple Sequence Repeats (SSRs) are short tandem repeats of DNA motifs present in all genomes. They have long been used for a variety of purposes in the areas of population genetics, genotyping, marker-assisted selection, and forensics. Numerous studies have highlighted their functional roles in genome organization and gene regulation. Read More

    Identifying structural variants using linked-read sequencing data.
    Bioinformatics 2017 Nov 3. Epub 2017 Nov 3.
    Department of Computer Science, Princeton University, Princeton, 08540, USA.
    Motivation: Structural variation, including large deletions, duplications, inversions, translocations, and other rearrangements, is common in human and cancer genomes. A number of methods have been developed to identify structural variants from Illumina short-read sequencing data. However, reliable identification of structural variants remains challenging because many variants have breakpoints in repetitive regions of the genome and thus are difficult to identify with short reads. Read More

    Effect of normalization methods on the performance of supervised learning algorithms applied to HTSeq-FPKM-UQ data sets: 7SK RNA expression as a predictor of survival in patients with colon adenocarcinoma.
    Brief Bioinform 2017 Nov 3. Epub 2017 Nov 3.
    Motivation: One of the main challenges in machine learning (ML) is choosing an appropriate normalization method. Here, we examine the effect of various normalization methods on analyzing FPKM upper quartile (FPKM-UQ) RNA sequencing data sets. We collect the HTSeq-FPKM-UQ files of patients with colon adenocarcinoma from TCGA-COAD project. Read More

    NanoStringNormCNV: Pre-processing of NanoString CNV data.
    Bioinformatics 2017 Nov 3. Epub 2017 Nov 3.
    Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Toronto, Canada.
    Summary: The NanoString System is a well-established technology for measuring RNA and DNA abundance. Although it can estimate copy number variation, relatively few tools support analysis of these data. To address this gap, we created NanoStringNormCNV, an R package for pre-processing and copy number variant calling from NanoString data. Read More

    Coloured Petri nets for multilevel, multiscale and multidimensional modelling of biological systems.
    Brief Bioinform 2017 Nov 3. Epub 2017 Nov 3.
    Owing to the availability of data of one biological phenomenon at different levels/scales, modelling of biological systems is moving from single level/scale to multiple levels/scales, which introduces a number of challenges. Coloured Petri nets (ColPNs) have been successfully applied to multilevel, multiscale and multidimensional modelling of some biological systems, addressing many of these challenges. In this article, we first review the basics of ColPNs and some popular extensions, and then their applications for multilevel, multiscale and multidimensional modelling of biological systems. Read More

    CommWalker: Correctly Evaluating Modules in Molecular Networks in Light of Annotation Bias.
    Bioinformatics 2017 Nov 3. Epub 2017 Nov 3.
    Department of Statistics, University of Oxford, Oxford, OX1 3LB, United Kingdom.
    Motivation: Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favour communities of well-studied proteins. Read More

    TabPath: interactive Tables for Metabolic Pathway analysis.
    Bioinformatics 2017 Nov 3. Epub 2017 Nov 3.
    Laboratório Multiusuário de Bioinformática, Núcleo de Pesquisas em Ciências Biológicas, Universidade Federal de Ouro Preto, Ouro Preto, MG - Brazil.
    Motivation: Information about metabolic pathways in a comparative context is one of the most powerful tool to help the understanding of genome-based differences in phenotypes among organisms. Although several platforms exist that provide a wealth of information on metabolic pathways of diverse organisms, the comparison among organisms using metabolic pathways is still a difficult task.

    Results: We present TabPath (Tables for Metabolic Pathway), a web-based tool to facilitate comparison of metabolic pathways in genomes based on KEGG. Read More

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