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Bioinformatics & Computational Biology

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Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively different computational methods and paradigms are needed...
October 21, 2016: Briefings in Bioinformatics
Jonathan D Wren, Inimary Toby, Huxiao Hong, Bindu Nanduri, Rakesh Kaundal, Mikhail G Dozmorov, Shraddha Thakkar
No abstract text is available yet for this article.
October 6, 2016: BMC Bioinformatics
Wei Lan, Min Li, Kaijie Zhao, Jin Liu, Fang-Xiang Wu, Yi Pan, Jianxin Wang
MOTIVATION: Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs) play important roles in many human diseases. Therefore, predicting novel lncRNA-disease associations would contribute to dissect the complex mechanisms of disease pathogenesis. Some computational methods have been developed to infer lncRNA-disease associations. However, most of these methods infer lncRNA-disease associations only based on single data resource. RESULTS: In this paper, we propose a new computational method to predict lncRNA-disease associations by integrating multiple biological data resources...
October 14, 2016: Bioinformatics
Patrick K O'Neill, Ivan Erill
BACKGROUND: Biological sequence motifs drive the specific interactions of proteins and nucleic acids. Accordingly, the effective computational discovery and analysis of such motifs is a central theme in bioinformatics. Many practical questions about the properties of motifs can be recast as random sampling problems. In this light, the task is to determine for a given motif whether a certain feature of interest is statistically unusual among relevantly similar alternatives. Despite the generality of this framework, its use has been frustrated by the difficulties of defining an appropriate reference class of motifs for comparison and of sampling from it effectively...
October 6, 2016: BMC Bioinformatics
David Ramírez
Due to the synergic relationship between medical chemistry, bioinformatics and molecular simulation, the development of new accurate computational tools for small molecules drug design has been rising over the last years. The main result is the increased number of publications where computational techniques such as molecular docking, de novo design as well as virtual screening have been used to estimate the binding mode, site and energy of novel small molecules. In this work I review some tools, which enable the study of biological systems at the atomistic level, providing relevant information and thereby, enhancing the process of rational drug design...
2016: Open Medicinal Chemistry Journal
Olivier B Poirion, Xun Zhu, Travers Ching, Lana Garmire
The emerging single-cell RNA-Seq (scRNA-Seq) technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution. It opens the door to reveal intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms. Parallel to improving experimental protocols to deal with technological issues, deriving new analytical methods to interpret the complexity in scRNA-Seq data is just as challenging...
2016: Frontiers in Genetics
Jesper Tegnér, Hector Zenil, Narsis A Kiani, Gordon Ball, David Gomez-Cabrero
Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics...
November 13, 2016: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
Iakov I Davydov, Marc Robinson-Rechavi, Nicolas Salamin
MOTIVATION: Codon models are widely used to identify the signature of selection at the molecular level and to test for changes in selective pressure during the evolution of genes encoding proteins. The large size of the state space of the Markov processes used to model codon evolution makes it difficult to use these models with large biological datasets. We propose here to use state aggregation to reduce the state space of codon models and, thus, improve the computational performance of likelihood estimation on these models...
October 2, 2016: Bioinformatics
Sascha Winter, Katharina Jahn, Stefanie Wehner, Leon Kuchenbecker, Manja Marz, Jens Stoye, Sebastian Böcker
Gene-order-based comparison of multiple genomes provides signals for functional analysis of genes and the evolutionary process of genome organization. Gene clusters are regions of co-localized genes on genomes of different species. The rapid increase in sequenced genomes necessitates bioinformatics tools for finding gene clusters in hundreds of genomes. Existing tools are often restricted to few (in many cases, only two) genomes, and often make restrictive assumptions such as short perfect conservation, conserved gene order or monophyletic gene clusters...
September 26, 2016: Nucleic Acids Research
Gleb Kichaev, Megan Roytman, Ruth Johnson, Eleazar Eskin, Sara Lindström, Peter Kraft, Bogdan Pasaniuc
MOTIVATION: Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation...
September 22, 2016: Bioinformatics
Pranjal Vachaspati, Tandy Warnow
MOTIVATION: The estimation of phylogenetic trees is a major part of many biological dataset analyses, but maximum likelihood approaches are NP-hard and Bayesian MCMC methods do not scale well to even moderate-sized datasets. Supertree methods, which are used to construct trees from trees computed on subsets, are critically important tools for enabling the statistical estimation of phylogenies for large and potentially heterogeneous datasets . Supertree estimation is itself NP-hard, and no current supertree method has sufficient accuracy and scalability to provide good accuracy on the large datasets that supertree methods were designed for, containing thousands of species and many subset trees...
September 23, 2016: Bioinformatics
Chunxuan Shao, Thomas Höfer
MOTIVATION: Single-cell transcriptome data provide unprecedented resolution to study heterogeneity in cell populations and present a challenge for unsupervised classification. Popular methods, like principal component analysis (PCA), often suffer from the high level of noise in the data. RESULTS: Here we adapt Nonnegative Matrix Factorization (NMF) to study the problem of identifying subpopulations in single-cell transcriptome data. In contrast to the conventional gene-centered view of NMF, identifying metagenes, we used NMF in a cell-centered direction, identifying cell subtypes ('metacells')...
September 23, 2016: Bioinformatics
Abdellah Tebani, Carlos Afonso, Stéphane Marret, Soumeya Bekri
The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations...
2016: International Journal of Molecular Sciences
Anuj Gupta, I King Jordan, Lavanya Rishishwar
: Rapid and accurate identification of the sequence type (ST) of bacterial pathogens is critical for epidemiological surveillance and outbreak control. Cheaper and faster next-generation sequencing (NGS) technologies have taken preference over the traditional method of amplicon sequencing for multilocus sequence typing (MLST). But data generated by NGS platforms necessitate quality control, genome assembly and sequence similarity searching before an isolate's ST can be determined. These are computationally intensive and time consuming steps, which are not ideally suited for real-time molecular epidemiology...
September 7, 2016: Bioinformatics
Václav Brázda, Jan Kolomazník, Jiří Lýsek, Lucia Hároníková, Jan Coufal, Jiří Št'astný
DNA cruciform structures play an important role in the regulation of natural processes including gene replication and expression, as well as nucleosome structure and recombination. They have also been implicated in the evolution and development of diseases such as cancer and neurodegenerative disorders. Cruciform structures are formed by inverted repeats, and their stability is enhanced by DNA supercoiling and protein binding. They have received broad attention because of their important roles in biology. Computational approaches to study inverted repeats have allowed detailed analysis of genomes...
September 30, 2016: Biochemical and Biophysical Research Communications
Ritu Rawal, Sonam Vijay, Kavita Kadian, Jagbir Singh, Veena Pande, Arun Sharma
In order to understand the importance of functional proteins in mosquito behavior, following blood meal, a baseline proteomic dataset is essential for providing insights into the physiology of blood feeding. Therefore, in this study as first step, in solution and 1-D electrophoresis digestion approach combined with tandem mass spectrometry (nano LC-MS/MS) and computational bioinformatics for data mining was used to prepare a baseline proteomic catalogue of salivary gland proteins of sugar fed An. culicifacies mosquitoes...
2016: PloS One
Max Sajitz-Hermstein, Nadine Töpfer, Sabrina Kleessen, Alisdair R Fernie, Zoran Nikoloski
MOTIVATION: Understanding the rerouting of metabolic reaction fluxes upon perturbations has the potential to link changes in molecular state of a cellular system to alteration of growth. Yet, differential flux profiling on a genome-scale level remains one of the biggest challenges in systems biology. This is particularly relevant in plants, for which fluxes in autotrophic growth necessitate time-consuming instationary labeling experiments and costly computations, feasible for small-scale networks...
September 1, 2016: Bioinformatics
Matthew Ruffalo, Ziv Bar-Joseph
MOTIVATION: Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease...
September 1, 2016: Bioinformatics
Sungyoung Lee, Sungkyoung Choi, Young Jin Kim, Bong-Jo Kim, Heungsun Hwang, Taesung Park
MOTIVATION: To address 'missing heritability' issue, many statistical methods for pathway-based analyses using rare variants have been proposed to analyze pathways individually. However, neglecting correlations between multiple pathways can result in misleading solutions, and pathway-based analyses of large-scale genetic datasets require massive computational burden. We propose a Pathway-based approach using HierArchical components of collapsed RAre variants Of High-throughput sequencing data (PHARAOH) for the analysis of rare variants by constructing a single hierarchical model that consists of collapsed gene-level summaries and pathways and analyzes entire pathways simultaneously by imposing ridge-type penalties on both gene and pathway coefficient estimates; hence our method considers the correlation of pathways without constraint by a multiple testing problem...
September 1, 2016: Bioinformatics
Muhammad Ammad-Ud-Din, Suleiman A Khan, Disha Malani, Astrid Murumägi, Olli Kallioniemi, Tero Aittokallio, Samuel Kaski
MOTIVATION: A key goal of computational personalized medicine is to systematically utilize genomic and other molecular features of samples to predict drug responses for a previously unseen sample. Such predictions are valuable for developing hypotheses for selecting therapies tailored for individual patients. This is especially valuable in oncology, where molecular and genetic heterogeneity of the cells has a major impact on the response. However, the prediction task is extremely challenging, raising the need for methods that can effectively model and predict drug responses...
September 1, 2016: Bioinformatics
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