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Bioinformatics

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https://www.readbyqxmd.com/read/29228294/accurate-mapping-of-trna-reads
#1
Anne Hoffmann, Jörg Fallmann, Mario Mörl, Peter F Stadler, Fabian Amman
Motivation: Many repetitive DNA elements are transcribed at appreciable expression levels. Mapping the corresponding RNA sequencing reads back to a reference genome is notoriously difficult and error-prone task, however. This is in particular true if chemical modifications introduce systematic mismatches, while at the same time the genomic loci are only approximately identical, as in the case of tRNAs. Results: We therefore developed a dedicated mapping strategy to handle RNA-seq reads that map to tRNAs relying on a modified target genome in which known tRNA loci are masked and instead intronless tRNA precursor sequences are appended as artificial "chromosomes"...
December 8, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228271/litpathexplorer-a-confidence-based-visual-text-analytics-tool-for-exploring-literature-enriched-pathway-models
#2
Axel J Soto, Chrysoula Zerva, Riza Batista-Navarro, Sophia Ananiadou
Motivation: Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. Results: We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i...
December 8, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228193/deepsf-deep-convolutional-neural-network-for-mapping-protein-sequences-to-folds
#3
Jie Hou, Badri Adhikari, Jianlin Cheng
Motivation: Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a target protein based on the fold of a template protein with known structure, which cannot explain the relationship between sequence and fold. Only a few methods had been developed to classify protein sequences into a small number of folds due to methodological limitations, which are not generally useful in practice...
December 8, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228186/aether-leveraging-linear-programming-for-optimal-cloud-computing-in-genomics
#4
Jacob M Luber, Braden T Tierney, Evan M Cofer, Chirag J Patel, Aleksandar D Kostic
Motivation: Across biology we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Results: Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective, and scalable framework that uses linear programming (LP) to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines...
December 8, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228185/dncon2-improved-protein-contact-prediction-using-two-level-deep-convolutional-neural-networks
#5
Badri Adhikari, Jie Hou, Jianlin Cheng
Motivation: Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key contributors to the recent progress in ab initio protein structure prediction, as demonstrated in the recent CASP experiments. Continuing the development of new methods to reliably predict contact maps is essential to further improve ab initio structure prediction...
December 8, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228285/matrix-factorization-based-data-fusion-for-the-prediction-of-lncrna-disease-associations
#6
Guangyuan Fu, Jun Wang, Carlotta Domeniconi, Guoxian Yu
Motivation: Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention, and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be...
December 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228191/frogs-find-rapidly-otus-with-galaxy-solution
#7
Frédéric Escudié, Lucas Auer, Maria Bernard, Mahendra Mariadassou, Laurent Cauquil, Katia Vidal, Sarah Maman, Guillermina Hernandez-Raquet, Sylvie Combes, Géraldine Pascal
Motivation: Metagenomics leads to major advances in microbial ecology and biologists need user friendly tools to analyze their data on their own. Results: This Galaxy-supported pipeline, called FROGS, is designed to analyze large sets of amplicon sequences and produce abundance tables of Operational Taxonomic Units (OTUs) and their taxonomic affiliation. The clustering uses Swarm. The chimera removal uses VSEARCH, combined with original cross-sample validation. The taxonomic affiliation returns an innovative multi-affiliation output to highlight databases conflicts and uncertainties...
December 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228182/peith-%C3%AE-perfecting-experiments-with-information-theory-in-python-with-gpu-support
#8
Leander Dony, Jonas Mackerodt, Scott Ward, Sarah Filippi, Michael P H Stumpf, Juliane Liepe
Motivation: Different experiments provide differing levels of information about a biological system. This makes it difficult, a priori, to select one of them beyond mere speculation and/or belief, especially when resources are limited. With the increasing diversity of experimental approaches and general advances in quantitative systems biology, methods that inform us about the information content that a given experiment carries about the question we want to answer, become crucial. Results: PEITH(Θ) is a general purpose, Python framework for experimental design in systems biology...
December 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228175/sana-netgo-a-combinatorial-approach-to-using-gene-ontology-go-terms-to-score-network-alignments
#9
Wayne B Hayes, Nil Mamano
Motivation: Gene Ontology (GO) terms are frequently used to score alignments between protein-protein interaction (PPI) networks. Methods exist to measure GO similarity between proteins in isolation, but proteins in a network alignment are not isolated: each pairing is dependent on every other via the alignment itself. Existing measures fail to take into account the frequency of GO terms across networks, instead imposing arbitrary rules on when to allow GO terms. Results: Here we develop NetGO, a new measure that naturally weighs infrequent, informative GO terms more heavily than frequent, less informative GO terms, without arbitrary cutoffs, instead downweighting GO terms according to their frequency in the networks being aligned...
December 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228172/spring-a-kinetic-interface-for-visualizing-high-dimensional-single-cell-expression-data
#10
Caleb Weinreb, Samuel Wolock, Allon Klein
Motivation: Single-cell gene expression profiling technologies can map the cell states in a tissue or organism. As these technologies become more common, there is a need for computational tools to explore the data they produce. In particular, visualizing continuous gene expression topologies can be improved, since current tools tend to fragment gene expression continua or capture only limited features of complex population topologies. Results: Force-directed layouts of k-nearest-neighbor graphs can visualize continuous gene expression topologies in a manner that preserves high-dimensional relationships and captures complex population topologies...
December 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228171/gene-graphics-a-genomic-neighborhood-data-visualization-web-application
#11
Katherine J Harrison, Valérie de Crécy-Lagard, Rémi Zallot
Summary: The examination of gene neighborhood is an integral part of comparative genomics but no tools to produce publication quality graphics of gene clusters are available. Gene Graphics is a straightforward web application for creating such visuals. Supported inputs include National Center for Biotechnology Information (NCBI) gene and protein identifiers with automatic fetching of neighboring information, GenBank files and data extracted from the SEED database. Gene representations can be customized for many parameters including gene and genome names, colors and sizes...
December 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29220513/integrating-5hmc-and-gene-expression-data-to-infer-regulatory-mechanisms
#12
Cristina Mitrea, Priyanga Wijesinghe, Greg Dyson, Adéle Kruger, Douglas M Ruden, Sorin Draghici, Aliccia Bollig-Fischer
Motivation: Epigenetic mechanisms are known to play a major role in breast cancer. However, the role of 5-hydroxymethylcytosine (5hmC) remains understudied. We hypothesize that 5hmC mediates redox regulation of gene expression in an aggressive subtype known as triple negative breast cancer (TNBC). To address this, our objective was to highlight genes that may be the target of this process by identifying redox-regulated, antioxidant-sensitive, gene-localized 5hmC changes associated with mRNA changes in TNBC cells...
December 6, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29220508/model-based-design-of-bistable-cell-factories-for-metabolic-engineering
#13
Shyam Srinivasan, William R Cluett, Radhakrishnan Mahadevan
Motivation: Metabolism can exhibit dynamic phenomena like bistability due to the presence of regulatory motifs like the positive feedback loop. As cell factories, microorganisms with bistable metabolism can have a high and a low product flux at the two stable steady states, respectively. The exclusion of metabolic regulation and network dynamics limits the ability of pseudo-steady state stoichiometric models to detect the presence of bistability, and reliably assess the outcomes of design perturbations to metabolic networks...
December 6, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29211828/asar-visual-analysis-of-metagenomes-in-r
#14
Askarbek Orakov, Nazgul Sakenova, Anatoly Sorokin, Igor Goryanin
Motivation: Functional and taxonomic analyses are critical steps in understanding interspecific interactions within microbial communities. Currently, such analyses are run separately, which complicates interpretation of results. Here we present the ASAR interactive tool for simultaneous analysis of metagenomic data in three dimensions: taxonomy, function, metagenome. Results: An interactive data analysis tool for selection, aggregation, and visualization of metagenomic data is presented...
December 1, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29211825/bicycle-a-bioinformatics-pipeline-to-analyze-bisulfite-sequencing-data
#15
Osvaldo Graña, Hugo López-Fernández, Florentino Fdez-Riverola, David González Pisano, Daniel Glez-Peña
Summary: High-throughput sequencing of bisulfite-converted DNA is a technique used to measure DNA methylation levels. Although a considerable number of computational pipelines have been developed to analyze such data, none of them tackles all the peculiarities of the analysis together, revealing limitations that can force the user to manually perform additional steps needed for a complete processing of the data. This article presents bicycle, an integrated, flexible analysis pipeline for bisulfite sequencing data...
December 1, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29211823/identifying-functionally-informative-evolutionary-sequence-profiles
#16
Nelson Gil, Andras Fiser
Motivation: Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain a biologically informative MSAs for such purposes is poorly-explored, and has traditionally been performed manually. Results: We present SAMMI, an automated, sequence-based approach to objectively select an optimal MSA from a large set of alternatives sampled from a general sequence database search...
December 1, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29206901/genssi-2-0-multi-experiment-structural-identifiability-analysis-of-sbml-models
#17
Thomas S Ligon, Fabian Fröhlich, Oana T Chi, Julio R Banga, Eva Balsa-Canto, Jan Hasenauer
Motivation: Mathematical modeling using ordinary differential equations (ODEs) is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ODE models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. Results: We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability)...
November 30, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29206899/mosaic-a-chemical-genetic-interaction-data-repository-and-web-resource-for-exploring-chemical-modes-of-action
#18
Justin Nelson, Scott W Simpkins, Hamid Safizadeh, Sheena C Li, Jeff S Piotrowski, Hiroyuki Hirano, Yoko Yashiroda, Hiroyuki Osada, Minoru Yoshida, Charles Boone, Chad L Myers
Summary: Chemical-genomic approaches that map interactions between small molecules and genetic perturbations offer a promising strategy for functional annotation of uncharacterized bioactive compounds. We recently developed a new high-throughput platform for mapping chemical-genetic (CG) interactions in yeast that can be scaled to screen large compound collections, and we applied this system to generate CG interaction profiles for more than 13,000 compounds. When integrated with the existing global yeast genetic interaction network, CG interaction profiles can enable mode-of-action prediction for previously uncharacterized compounds as well as discover unexpected secondary effects for known drugs...
November 30, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29194470/idingo-integrative-differential-network-analysis-in-genomics-with-shiny-application
#19
Caleb A Class, Min Jin Ha, Veerabhadran Baladandayuthapani, Kim-Anh Do
Motivation: Differential network analysis is an important way to understand network rewiring involved in disease progression and development. Building differential networks from multiple `omics data provides insight into the holistic differences of the interactive system under different patient-specific groups. DINGO was developed to infer group-specific dependencies and build differential networks. However, DINGO and other existing tools are limited to analyze data arising from a single platform, and modeling each of the multiple 'omics data independently does not account for the hierarchical structure of the data...
November 29, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29194469/biobakery-a-meta-omic-analysis-environment
#20
Lauren J McIver, Galeb Abu-Ali, Eric A Franzosa, Randall Schwager, Xochitl C Morgan, Levi Waldron, Nicola Segata, Curtis Huttenhower
Summary: bioBakery is a meta'omic analysis environment and collection of individual software tools with the capacity to process raw shotgun sequencing data into actionable microbial community feature profiles, summary reports, and publication-ready figures. It includes a collection of pre-configured analysis modules also joined into workflows for reproducibility. Availability: bioBakery (http://huttenhower.sph.harvard.edu/biobakery) is publicly available for local installation as individual modules and as a virtual machine image...
November 29, 2017: Bioinformatics
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