23,725 results match your criteria Bioinformatics[Journal]


Estimates of introgression as a function of pairwise distances.

BMC Bioinformatics 2019 Apr 23;20(1):207. Epub 2019 Apr 23.

Department of Entomology and Center for Comparative Genomics, Institute for Biodiversity Science and Sustainability, California Academy of Sciences, 55 Music Concourse Dr., San Francisco, USA.

Background: Research over the last 10 years highlights the increasing importance of hybridization between species as a major force structuring the evolution of genomes and potentially providing raw material for adaptation by natural and/or sexual selection. Fueled by research in a few model systems where phenotypic hybrids are easily identified, research into hybridization and introgression (the flow of genes between species) has exploded with the advent of whole-genome sequencing and emerging methods to detect the signature of hybridization at the whole-genome or chromosome level. Amongst these are a general class of methods that utilize patterns of single-nucleotide polymorphisms (SNPs) across a tree as markers of hybridization. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2747-zDOI Listing
April 2019
1 Read

A network-based approach for identifying suitable biomarkers for oral immunotherapy of food allergy.

BMC Bioinformatics 2019 Apr 23;20(1):206. Epub 2019 Apr 23.

TNO, PO Box 360, 3700, AJ, Zeist, The Netherlands.

Background: Oral immunotherapy (OIT) is a promising therapeutic approach to treat food allergic patients. However, concerns with regards to safety and long-term efficacy of OIT remain. There is a need to identify biomarkers that predict, monitor and/or evaluate the effects of OIT. Read More

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http://dx.doi.org/10.1186/s12859-019-2802-9DOI Listing

Detailed prediction of protein sub-nuclear localization.

BMC Bioinformatics 2019 Apr 23;20(1):205. Epub 2019 Apr 23.

Department of Informatics, Bioinformatics & Computational Biology - i12, TUM (Technical University of Munich), Boltzmannstr. 3, 85748, Garching/Munich, Germany.

Background: Sub-nuclear structures or locations are associated with various nuclear processes. Proteins localized in these substructures are important to understand the interior nuclear mechanisms. Despite advances in high-throughput methods, experimental protein annotations remain limited. Read More

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http://dx.doi.org/10.1186/s12859-019-2790-9DOI Listing

Tiling Nussinov's RNA folding loop nest with a space-time approach.

BMC Bioinformatics 2019 Apr 24;20(1):208. Epub 2019 Apr 24.

West Pomeranian University of Technology, Faculty of Computer Science, Zolnierska 49, Szczecin, 71-210, Poland.

Background: An RNA primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC (adenine, uracil, guanine, cytosine). The strand can be folded onto itself, i.e. Read More

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http://dx.doi.org/10.1186/s12859-019-2785-6DOI Listing

BHap: a novel approach for bacterial haplotype reconstruction.

Bioinformatics 2019 Apr 20. Epub 2019 Apr 20.

Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, FL, USA.

Motivation: The bacterial haplotype reconstruction is critical for selecting proper treatments for diseases caused by unknown haplotypes. Existing methods and tools do not work well on this task, because they are usually developed for viral instead of bacterial populations.

Results: In this study, we developed BHap, a novel algorithm based on fuzzy flow networks, for reconstructing bacterial haplotypes from next generation sequencing data. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz280DOI Listing
April 2019
1 Read

The EntOptLayout Cytoscape plug-in for the efficient visualization of major protein complexes in protein-protein interaction and signalling networks.

Bioinformatics 2019 Apr 20. Epub 2019 Apr 20.

Network Science Institute, Northeastern University, Boston MA, USA.

Motivation: Network visualizations of complex biological datasets usually result in 'hairball' images, which do not discriminate network modules.

Results: We present the EntOptLayout Cytoscape plug-in based on a recently developed network representation theory. The plug-in provides an efficient visualization of network modules, which represent major protein complexes in protein-protein interaction and signalling networks. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz257DOI Listing

FuncTree2: an interactive radial tree for functional hierarchies and omics data visualization.

Bioinformatics 2019 Apr 20. Epub 2019 Apr 20.

Department of Life Science and Technology, Tokyo Institute of Technology, Tokyo, Japan.

Summary: Functional annotations and their hierarchical classification are widely used in omics workflows to build novel insight upon existing biological knowledge. Currently, a plethora of tools is available to explore omics datasets at the level of functional annotations, but there is a lack of feature rich and user-friendly tools that help scientists take advantage of their hierarchical classification for additional and often invaluable insights. Here we present FuncTree2, a user-friendly web application that turns hierarchical classifications into interactive and highly customizable radial trees, and enables researchers to visualize their data simultaneously on all its levels. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz245DOI Listing

ORCA: A Comprehensive Bioinformatics Container Environment for Education and Research.

Bioinformatics 2019 Apr 20. Epub 2019 Apr 20.

Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada.

Summary: The ORCA bioinformatics environment is a Docker image that contains hundreds of bioinformatics tools and their dependencies. The ORCA image and accompanying server infrastructure provide a comprehensive bioinformatics environment for education and research. The ORCA environment on a server is implemented using Docker containers, but without requiring users to interact directly with Docker, suitable for novices who may not yet have familiarity with managing containers. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz278DOI Listing

A framework for space-efficient variable-order Markov models.

Bioinformatics 2019 Apr 20. Epub 2019 Apr 20.

CAPA, DTISI, Centre de Recherche sur l'Information Scientifique et Technique, Algiers, Algeria.

Motivation: Markov models with contexts of variable length are widely used in bioinformatics for representing sets of sequences with similar biological properties. When models contain many long contexts, existing implementations are either unable to handle genome-scale training datasets within typical memory budgets, or they are optimized for specific model variants and are thus inflexible.

Results: We provide practical, versatile representations of variable-order Markov models and of interpolated Markov models, that support a large number of context-selection criteria, scoring functions, probability smoothing methods, and interpolations, and that take up to four times less space than previous implementations based on the suffix array, regardless of the number and length of contexts, and up to ten times less space than previous trie-based representations, or more, while matching the size of related, state-of-the-art data structures from Natural Language Processing. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz268DOI Listing
April 2019
1 Read

PGxO and PGxLOD: a reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):139. Epub 2019 Apr 18.

Université de Lorraine, CNRS, Inria, LORIA, Nancy, 54000, France.

Background: Pharmacogenomics (PGx) studies how genomic variations impact variations in drug response phenotypes. Knowledge in pharmacogenomics is typically composed of units that have the form of ternary relationships gene variant - drug - adverse event. Such a relationship states that an adverse event may occur for patients having the specified gene variant and being exposed to the specified drug. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2693-9DOI Listing
April 2019
4 Reads

decompTumor2Sig: identification of mutational signatures active in individual tumors.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):152. Epub 2019 Apr 18.

Institute of Computer Science and Institute of Bioinformatics, Freie Universität Berlin, Berlin, Germany.

Background: The somatic mutations found in a tumor have in most cases been caused by multiple mutational processes such as those related to extrinsic carcinogens like cigarette smoke, and those related to intrinsic processes like age-related spontaneous deamination of 5-methylcytosine. The effect of such mutational processes can be modeled by mutational signatures, of which two different conceptualizations exist: the model introduced by Alexandrov et al., Nature 500:415-421, 2013, and the model introduced by Shiraishi et al. Read More

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http://dx.doi.org/10.1186/s12859-019-2688-6DOI Listing
April 2019
4 Reads

A Dynamic Bayesian Network model for the simulation of Amyotrophic Lateral Sclerosis progression.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):118. Epub 2019 Apr 18.

Department of Information Engineering, University of Padova, Gradenigo 6/b, 35131, Padova, Italy.

Background: Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease progressively affecting upper and lower motor neurons in the brain and spinal cord. Mean life expectancy is three to five years, with paralysis of muscles, respiratory failure and loss of vital functions being the common causes of death. Clinical manifestations of ALS are heterogeneous due to the mix of anatomic regions involvement and the variability in disease course; consequently, diagnosis and prognosis at the level of individual patient is really challenging. Read More

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http://dx.doi.org/10.1186/s12859-019-2692-xDOI Listing

An algebraic language for RNA pseudoknots comparison.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):161. Epub 2019 Apr 18.

School of Science and Technology, University of Camerino, Via Madonna della Carceri 9, Camerino, 62032, Italy.

Background: RNA secondary structure comparison is a fundamental task for several studies, among which are RNA structure prediction and evolution. The comparison can currently be done efficiently only for pseudoknot-free structures due to their inherent tree representation.

Results: In this work, we introduce an algebraic language to represent RNA secondary structures with arbitrary pseudoknots. Read More

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http://dx.doi.org/10.1186/s12859-019-2689-5DOI Listing

Analyzing big datasets of genomic sequences: fast and scalable collection of k-mer statistics.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):138. Epub 2019 Apr 18.

Dipartimento di Matematica ed Informatica, Università di Palermo, Palermo, 90133, Italy.

Background: Distributed approaches based on the MapReduce programming paradigm have started to be proposed in the Bioinformatics domain, due to the large amount of data produced by the next-generation sequencing techniques. However, the use of MapReduce and related Big Data technologies and frameworks (e.g. Read More

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http://dx.doi.org/10.1186/s12859-019-2694-8DOI Listing

Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):119. Epub 2019 Apr 18.

geneXplain GmbH, 38302, Wolfenbüttel, Germany.

Background: The search for molecular biomarkers of early-onset colorectal cancer (CRC) is an important but still quite challenging and unsolved task. Detection of CpG methylation in human DNA obtained from blood or stool has been proposed as a promising approach to a noninvasive early diagnosis of CRC. Thousands of abnormally methylated CpG positions in CRC genomes are often located in non-coding parts of genes. Read More

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http://dx.doi.org/10.1186/s12859-019-2687-7DOI Listing

The 2017 Network Tools and Applications in Biology (NETTAB) workshop: aims, topics and outcomes.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):125. Epub 2019 Apr 18.

ICAR-CNR, Institute for high performance computing and networking, National Research Council of Italy, Palermo, 90146, Italy.

The 17th International NETTAB workshop was held in Palermo, Italy, on October 16-18, 2017. The special topic for the meeting was "Methods, tools and platforms for Personalised Medicine in the Big Data Era", but the traditional topics of the meeting series were also included in the event. About 40 scientific contributions were presented, including four keynote lectures, five guest lectures, and many oral communications and posters. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2681-0DOI Listing
April 2019
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Greedy de novo motif discovery to construct motif repositories for bacterial proteomes.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):141. Epub 2019 Apr 18.

Faculty of Science, Institute for Computational Science, University of Zurich, 429 Winterthurerstrasse, 190, Zurich, CH-8057, Switzerland.

Background: Bacterial surfaces are complex systems, constructed from membranes, peptidoglycan and, importantly, proteins. The proteins play crucial roles as critical regulators of how the bacterium interacts with and survive in its environment. A full catalog of the motifs in protein families and their relative conservation grade is a prerequisite to target the protein-protein interaction that bacterial surface protein makes to host proteins. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2686-8DOI Listing
April 2019
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Integration of transcriptomic data in a genome-scale metabolic model to investigate the link between obesity and breast cancer.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):162. Epub 2019 Apr 18.

High Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, Napoli, 80131, Italy.

Background: Obesity is a complex disorder associated with an increased risk of developing several comorbid chronic diseases, including postmenopausal breast cancer. Although many studies have investigated this issue, the link between body weight and either risk or poor outcome of breast cancer is still to characterize. Systems biology approaches, based on the integration of multiscale models and data from a wide variety of sources, are particularly suitable for investigating the underlying molecular mechanisms of complex diseases. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2685-9DOI Listing
April 2019
3 Reads

FEDRO: a software tool for the automatic discovery of candidate ORFs in plants with c →u RNA editing.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):124. Epub 2019 Apr 18.

LMCB, MRC, Cell Biology Unit and Department of Developmental Biology, University College, London, UK.

Background: RNA editing is an important mechanism for gene expression in plants organelles. It alters the direct transfer of genetic information from DNA to proteins, due to the introduction of differences between RNAs and the corresponding coding DNA sequences. Software tools successful for the search of genes in other organisms not always are able to correctly perform this task in plants organellar genomes. Read More

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http://dx.doi.org/10.1186/s12859-019-2696-6DOI Listing

VIGLA-M: visual gene expression data analytics.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):150. Epub 2019 Apr 18.

Khaos Research, Universidad de Málaga, Málaga, Spain, Arquitecto Francisco Peñalosa 18, Málaga, 29071, Spain.

Background: The analysis of gene expression levels is used in many clinical studies to know how patients evolve or to find new genetic biomarkers that could help in clinical decision making. However, the techniques and software available for these analyses are not intended for physicians, but for geneticists. However, enabling physicians to make initial discoveries on these data would benefit in the clinical assay development. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2695-7DOI Listing
April 2019
2 Reads

GenHap: a novel computational method based on genetic algorithms for haplotype assembly.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):172. Epub 2019 Apr 18.

Department of Informatics, Systems and Communication (DISCo), University of Milano-Bicocca, Viale Sarca 336, U14 Building, Milan, 20126, Italy.

Background: In order to fully characterize the genome of an individual, the reconstruction of the two distinct copies of each chromosome, called haplotypes, is essential. The computational problem of inferring the full haplotype of a cell starting from read sequencing data is known as haplotype assembly, and consists in assigning all heterozygous Single Nucleotide Polymorphisms (SNPs) to exactly one of the two chromosomes. Indeed, the knowledge of complete haplotypes is generally more informative than analyzing single SNPs and plays a fundamental role in many medical applications. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2691-yDOI Listing
April 2019
1 Read

RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):120. Epub 2019 Apr 18.

Istituto di Biomedicina ed Immunologia Molecolare (IBIM) CNR, via Ugo la Malfa 153, 90146, Palermo, Italy.

Background: MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell line. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2683-yDOI Listing
April 2019
1 Read

Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):173. Epub 2019 Apr 18.

Computer Science Department, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, D-03046, Germany.

Background: Quorum sensing drives biofilm formation in bacteria in order to ensure that biofilm formation only occurs when colonies are of a sufficient size and density. This spatial behaviour is achieved by the broadcast communication of an autoinducer in a diffusion scenario. This is of interest, for example, when considering the role of gut microbiota in gut health. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2690-zDOI Listing
April 2019
1 Read

From trash to treasure: detecting unexpected contamination in unmapped NGS data.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):168. Epub 2019 Apr 18.

High Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, Napoli, 80131, Italy.

Background: Next Generation Sequencing (NGS) experiments produce millions of short sequences that, mapped to a reference genome, provide biological insights at genomic, transcriptomic and epigenomic level. Typically the amount of reads that correctly maps to the reference genome ranges between 70% and 90%, leaving in some cases a consistent fraction of unmapped sequences. This 'misalignment' can be ascribed to low quality bases or sequence differences between the sample reads and the reference genome. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2684-xDOI Listing
April 2019
1 Read

Metabolic and signalling network maps integration: application to cross-talk studies and omics data analysis in cancer.

BMC Bioinformatics 2019 Apr 18;20(Suppl 4):140. Epub 2019 Apr 18.

Institut Curie, 26 rue d'Ulm, F-75005, Paris, France.

Background: The interplay between metabolic processes and signalling pathways remains poorly understood. Global, detailed and comprehensive reconstructions of human metabolism and signalling pathways exist in the form of molecular maps, but they have never been integrated together. We aim at filling in this gap by integrating of both signalling and metabolic pathways allowing a visual exploration of multi-level omics data and study of cross-regulatory circuits between these processes in health and in disease. Read More

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http://dx.doi.org/10.1186/s12859-019-2682-zDOI Listing
April 2019
2 Reads

Evolution of biosequence search algorithms: a brief survey.

Authors:
Gregory Kucherov

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

CNRS and LIGM/University of Paris-Est, Marne-la-Vallée, France.

Motivation: Although modern high-throughput biomolecular technologies produce various types of data, biosequence data remains at the core of bioinformatic analyses. However, computational techniques for dealing with this data evolved dramatically.

Results: In this bird's-eye review, we overview the evolution of main algorithmic techniques for comparing and searching biological sequences. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz272DOI Listing

DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning.

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

School of Information Science and Engineering, Central South University, Changsha, China.

Motivation: The Oxford Nanopore sequencing enables to directly detect methylation states of bases in DNA from reads without extra laboratory techniques. Novel computational methods are required to improve the accuracy and robustness of DNA methylation state prediction using Nanopore reads.

Results: In this study, we develop DeepSignal, a deep learning method to detect DNA methylation states from Nanopore sequencing reads. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz276DOI Listing
April 2019
2 Reads

Overlap graph-based generation of haplotigs for diploids and polyploids.

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

Centrum Wiskunde & Informatica, Amsterdam, Netherlands.

Motivation: Haplotype aware genome assembly plays an important role in genetics, medicine, and various other disciplines, yet generation of haplotype-resolved de novo assemblies remains a major challenge. Beyond distinguishing between errors and true sequential variants, one needs to assign the true variants to the different genome copies. Recent work has pointed out that the enormous quantities of traditional NGS read data have been greatly underexploited in terms of haplotig computation so far, which reflects that methodology for reference independent haplotig computation has not yet reached maturity. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz255DOI Listing
April 2019
1 Read

Hybrid analysis of gene dynamics predicts context specific expression and offers regulatory insights.

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

Interdisciplinary Biological Sciences, Northwestern University, Evanston, IL.

Motivation: To understand the regulatory pathways underlying diseases, studies often investigate the differential gene expression between genetically or chemically differing cell populations. Differential expression analysis identifies global changes in transcription and enables the inference of functional roles of applied perturbations. This approach has transformed the discovery of genetic drivers of disease and possible therapies. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz256DOI Listing

Fast detection of maximal exact matches via fixed sampling of query k-mers and Bloom filtering of index k-mers.

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

Advanced Analytics Institute, Faculty of Engineering and IT, University of Technology Sydney, Australia.

Motivation: Detection of maximal exact matches (MEMs) between two long sequences is a fundamental problem in pairwise reference-query genome comparisons. To efficiently compare larger and larger genomes, reducing the number of indexed k-mers as well as the number of query k-mers has been adopted as a mainstream approach which saves the computational resources by avoiding a significant number of unnecessary matches.

Results: Under this framework, we proposed a new method to detect all MEMs from a pair of genomes. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz273DOI Listing

Computational identification of prion-like RNA-binding proteins that form liquid phase-separated condensates.

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium.

Motivation: Eukaryotic cells contain different membrane-delimited compartments, which are crucial for the biochemical reactions necessary to sustain cell life. Recent studies showed that cells can also trigger the formation of membraneless organelles composed by phase-separated proteins to respond to various stimuli. These condensates provide new ways to control the reactions and phase-separation proteins (PSPs) are thus revolutionising how cellular organization is conceived. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz274DOI Listing

Graph-Based data integration from bioactive peptide databases of pharmaceutical interest: towards an organized collection enabling visual network analysis.

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

Departamento de Ciencias de la Computación, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Baja California, Mexico.

Motivation: Bioactive peptides have gained great attention in the academy and pharmaceutical industry since they play an important role in human health. However, the increasing number of bioactive peptide databases is causing the problem of data redundancy and duplicated efforts. Even worse is the fact that the available data is non-standardized and often dirty with data entry errors. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz260DOI Listing

PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning.

Bioinformatics 2019 Apr 17. Epub 2019 Apr 17.

School of Computer Science and Technology, Tianjin University, Tianjin, China.

Motivation: Prediction of therapeutic peptides is critical for the discovery of novel and efficient peptide-based therapeutics. Computational methods, especially machine learning based methods, have been developed for addressing this need. However, most of existing methods are peptide-specific; currently, there is no generic predictor for multiple peptide types. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz246DOI Listing

Automatic Curation of Large Comparative Animal MicroRNA Data Sets.

Bioinformatics 2019 Apr 16. Epub 2019 Apr 16.

Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Härtelstraße 16-18, Leipzig, Germany.

Motivation: MicroRNAs form an important class of RNA regulators that has been studied extensively. The miRBase and Rfam database provide rich, frequently updated information on both pre-miRNAs and their mature forms. These data sources, however, rely on individual data submission and thus are neither complete nor consistent in their coverage across different miRNA families. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz271DOI Listing

Spliceogen: An integrative, scalable tool for the discovery of splice-altering variants.

Bioinformatics 2019 Apr 16. Epub 2019 Apr 16.

Victor Chang Cardiac Research Institute, Sydney, Australia.

Motivation: In silico prediction tools are essential for identifying variants which create or disrupt cis splicing motifs. However, there are limited options for genome-scale discovery of splice-altering variants.

Results: We have developed Spliceogen, a highly scalable pipeline integrating predictions from some of the individually best performing models for splice motif prediction: MaxEntScan, GeneSplicer, ESRseq and Branchpointer. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz263DOI Listing
April 2019
2 Reads

Discovering novel mutation signatures by latent Dirichlet allocation with variational Bayes inference.

Bioinformatics 2019 Apr 16. Epub 2019 Apr 16.

Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University.

Background: A cancer genome includes many mutations derived from various mutagens and mutational processes, leading to specific mutation patterns. It is known that each mutational process leads to characteristic mutations, and when a mutational process has preferences for mutations, this situation is called a "mutation signature." Identification of mutation signatures is an important task for elucidation of carcinogenic mechanisms. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz266DOI Listing

PyPore: a python toolbox for nanopore sequencing data handling.

Bioinformatics 2019 Apr 16. Epub 2019 Apr 16.

Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.

Motivation: The recent technological improvement of Oxford Nanopore sequencing pushed the throughput of these devices to 10-20 Gb allowing the generation of millions of reads. For these reasons, the availability of fast software packages for evaluating experimental quality by generating highly informative and interactive summary plots is of fundamental importance.

Results: We developed PyPore, a three module python toolbox designed to handle raw FAST5 files from quality checking to alignment to a reference genome and to explore their features through the generation of browsable HTML files. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz269DOI Listing

A new statistic for efficient detection of repetitive sequences.

Bioinformatics 2019 Apr 16. Epub 2019 Apr 16.

Department of Automation, MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, BNRist, Tsinghua University, Beijing, China.

Motivation: Detecting sequences containing repetitive regions is a basic bioinformatics task with many applications. Several methods have been developed for various types of repeat detection tasks. An efficient generic method for detecting most types of repetitive sequences is still desirable. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz262DOI Listing
April 2019
1 Read

Metabopolis: scalable network layout for biological pathway diagrams in urban map style.

BMC Bioinformatics 2019 Apr 15;20(1):187. Epub 2019 Apr 15.

Research Division of Computer Graphics, Institute of Visual Computing and Human- Centered Technology, TU Wien, Vienna, Austria.

Background: Biological pathways represent chains of molecular interactions in biological systems that jointly form complex dynamic networks. The network structure changes from the significance of biological experiments and layout algorithms often sacrifice low-level details to maintain high-level information, which complicates the entire image to large biochemical systems such as human metabolic pathways.

Results: Our work is inspired by concepts from urban planning since we create a visual hierarchy of biological pathways, which is analogous to city blocks and grid-like road networks in an urban area. Read More

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http://dx.doi.org/10.1186/s12859-019-2779-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466808PMC
April 2019
2 Reads

eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models.

BMC Bioinformatics 2019 Apr 16;20(1):189. Epub 2019 Apr 16.

Trans-NIH Center for Human Immunology (CHI), National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.

Background: Regularized generalized linear models (GLMs) are popular regression methods in bioinformatics, particularly useful in scenarios with fewer observations than parameters/features or when many of the features are correlated. In both ridge and lasso regularization, feature shrinkage is controlled by a penalty parameter λ. The elastic net introduces a mixing parameter α to tune the shrinkage continuously from ridge to lasso. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2778-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469092PMC
April 2019
1 Read

metamicrobiomeR: an R package for analysis of microbiome relative abundance data using zero-inflated beta GAMLSS and meta-analysis across studies using random effects models.

BMC Bioinformatics 2019 Apr 16;20(1):188. Epub 2019 Apr 16.

Gertrude H. Sergievsky Center, Columbia University, New York City, NY, USA.

Background: The rapid growth of high-throughput sequencing-based microbiome profiling has yielded tremendous insights into human health and physiology. Data generated from high-throughput sequencing of 16S rRNA gene amplicons are often preprocessed into composition or relative abundance. However, reproducibility has been lacking due to the myriad of different experimental and computational approaches taken in these studies. Read More

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http://dx.doi.org/10.1186/s12859-019-2744-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469060PMC

Effect of stochasticity on coinfection dynamics of respiratory viruses.

BMC Bioinformatics 2019 Apr 16;20(1):191. Epub 2019 Apr 16.

Department of Physics & Astronomy, Texas Christian University, Fort Worth, TX, USA.

Background: Respiratory viral infections are a leading cause of mortality worldwide. As many as 40% of patients hospitalized with influenza-like illness are reported to be infected with more than one type of virus. However, it is not clear whether these infections are more severe than single viral infections. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2793-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469119PMC
April 2019
2 Reads

Ryūtō: network-flow based transcriptome reconstruction.

BMC Bioinformatics 2019 Apr 16;20(1):190. Epub 2019 Apr 16.

Bioinformatics Group, Department of Computer Science & Interdisciplinary Center for Bioinformatics, Universität Leipzig, Härtelstraße 16-18, Leipzig, 04107, Germany.

Background: The rapid increase in High-throughput sequencing of RNA (RNA-seq) has led to tremendous improvements in the detection and reconstruction of both expressed coding and non-coding RNA transcripts. Yet, the complete and accurate annotation of the complex transcriptional output of not only the human genome has remained elusive. One of the critical bottlenecks in this endeavor is the computational reconstruction of transcript structures, due to high noise levels, technological limits, and other biases in the raw data. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
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http://dx.doi.org/10.1186/s12859-019-2786-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469118PMC
April 2019
1 Read

SurVIndel: improving CNV calling from high-throughput sequencing data through statistical testing.

Bioinformatics 2019 Apr 15. Epub 2019 Apr 15.

School of Computing, National University of Singapore, 13 Computing Drive, Singapore.

Motivation: Structural variations (SV) are large scale mutations in a genome; although less frequent than point mutations, due to their large size they are responsible for more heritable differences between individuals. Two prominent classes of SVs are deletions and tandem duplications. They play important roles in many devastating genetic diseases, such as Smith-Magenis syndrome, Potocki-Lupski syndrome and Williams-Beuren syndrome. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz261DOI Listing
April 2019
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IsoformSwitchAnalyzeR: Analysis of changes in genome-wide patterns of alternative splicing and its functional consequences.

Bioinformatics 2019 Apr 15. Epub 2019 Apr 15.

The Bioinformatics Centre, Department of Biology and Biotech Research & Innovation Centre, University of Copenhagen, Ole Maaløes Vej 5, DK, Copenhagen N, Denmark.

Summary: Alternative splicing is an important mechanism involved in both health and disease. Recent work highlights the importance of investigating genome-wide changes in patters of splicing and the subsequent functional consequences. Current computational methods only support such analysis on a gene-by-gene basis. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz247DOI Listing

Identifying centromeric satellites with dna-brnn.

Authors:
Heng Li

Bioinformatics 2019 Apr 15. Epub 2019 Apr 15.

Department of data sciences, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, USA.

Summary: Human alpha satellite and satellite 2/3 contribute to several percent of the human genome. However, identifying these sequences with traditional algorithms is computationally intensive. Here we develop dna-brnn, a recurrent neural network to learn the sequences of the two classes of centromeric repeats. Read More

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https://academic.oup.com/bioinformatics/advance-article/doi/
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http://dx.doi.org/10.1093/bioinformatics/btz264DOI Listing
April 2019
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Biomedical Image Augmentation Using Augmentor.

Bioinformatics 2019 Apr 15. Epub 2019 Apr 15.

Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Austria.

Motivation: Image augmentation is a frequently used technique in computer vision and has been seeing increased interest since the popularity of deep learning. Its usefulness is becoming more and more recognised due to deep neural networks requiring larger amounts of data to train, and because in certain fields, such as biomedical imaging, large amounts of labelled data are difficult to come by or expensive to produce. In biomedical imaging, features specific to this domain need to be addressed. Read More

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http://dx.doi.org/10.1093/bioinformatics/btz259DOI Listing

Highly efficient hypothesis testing methods for regression-type tests with correlated observations and heterogeneous variance structure.

BMC Bioinformatics 2019 Apr 15;20(1):185. Epub 2019 Apr 15.

Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Ave, Rochester, Rochester 14642, NY, USA.

Background: For many practical hypothesis testing (H-T) applications, the data are correlated and/or with heterogeneous variance structure. The regression t-test for weighted linear mixed-effects regression (LMER) is a legitimate choice because it accounts for complex covariance structure; however, high computational costs and occasional convergence issues make it impractical for analyzing high-throughput data. In this paper, we propose computationally efficient parametric and semiparametric tests based on a set of specialized matrix techniques dubbed as the PB-transformation. Read More

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http://dx.doi.org/10.1186/s12859-019-2783-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466736PMC

FGMP: assessing fungal genome completeness.

BMC Bioinformatics 2019 Apr 15;20(1):184. Epub 2019 Apr 15.

Department of Microbiology & Plant Pathology and Institute for Integrative Genome Biology, University of California-Riverside, Riverside, CA, 92521, USA.

Background: Inexpensive high-throughput DNA sequencing has democratized access to genetic information for most organisms so that research utilizing a genome or transcriptome of an organism is not limited to model systems. However, the quality of the assemblies of sampled genomes can vary greatly which hampers utility for comparisons and meaningful interpretation. The uncertainty of the completeness of a given genome sequence can limit feasibility of asserting patterns of high rates of gene loss reported in many lineages. Read More

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186
Publisher Site
http://dx.doi.org/10.1186/s12859-019-2782-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466665PMC
April 2019
1 Read