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Bioinformatics & Computational Biology

Emilie Neveu, Petr Popov, Alexandre Hoffmann, Angelo Migliosi, Xavier Besseron, Grégoire Danoy, Pascal Bouvry, Sergei Grudinin
Motivation: The root mean square deviation (RMSD) is one of the most used similarity criteria in structural biology and bioinformatics. Standard computation of the RMSD has a linear complexity with respect to the number of atoms in a molecule, making RMSD calculations time-consuming for the large-scale modeling applications, such as assessment of molecular docking predictions or clustering of spatially proximate molecular conformations. Previously we introduced the RigidRMSD algorithm to compute the RMSD corresponding to the rigid-body motion of a molecule...
March 15, 2018: Bioinformatics
Clément Niel, Christine Sinoquet, Christian Dina, Ghislain Rocheleau
Motivation: Large scale genome-wide association studies (GWAS) are tools of choice for discovering associations between genotypes and phenotypes. To date, many studies rely on univariate statistical tests for association between the phenotype and each assayed single nucleotide polymorphism (SNP). However, interaction between SNPs, namely epistasis, must be considered when tackling the complexity of underlying biological mechanisms. Epistasis analysis at large scale entails a prohibitive computational burden when addressing the detection of more than two interacting SNPs...
March 14, 2018: Bioinformatics
Nika Abdollahi, Alexandre Albani, Eric Anthony, Agnes Baud, Mélissa Cardon, Robert Clerc, Dariusz Czernecki, Romain Conte, Laurent David, Agathe Delaune, Samia Djerroud, Pauline Fourgoux, Nadège Guiglielmoni, Jeanne Laurentie, Nathalie Lehmann, Camille Lochard, Rémi Montagne, Vasiliki Myrodia, Vaitea Opuu, Elise Parey, Lélia Polit, Sylvain Privé, Chloé Quignot, Maria Ruiz-Cuevas, Mariam Sissoko, Nicolas Sompairac, Audrey Vallerix, Violaine Verrecchia, Marc Delarue, Raphael Guérois, Yann Ponty, Sophie Sacquin-Mora, Alessandra Carbone, Christine Froidevaux, Stéphane Le Crom, Olivier Lespinet, Martin Weigt, Samer Abboud, Juliana Bernardes, Guillaume Bouvier, Chloé Dequeker, Arnaud Ferré, Patrick Fuchs, Gaëlle Lelandais, Pierre Poulain, Hugues Richard, Hugo Schweke, Elodie Laine, Anne Lopes
We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product...
March 2018: PLoS Computational Biology
Azam Peyvandipour, Nafiseh Saberian, Adib Shafi, Michele Donato, Sorin Draghici
Motivation: Identification of novel therapeutic effects for existing U.S. Food and Drug Administration (FDA)-approved drugs, drug repurposing, is an approach aimed to dramatically shorten the drug discovery process, which is costly, slow and risky. Several computational approaches use transcriptional data to find potential repurposing candidates. The main hypothesis of such approaches is that if gene expression signature of a particular drug is opposite to the gene expression signature of a disease, that drug may have a potential therapeutic effect on the disease...
March 9, 2018: Bioinformatics
Nikolaos Tsiantis, Eva Balsa-Canto, Julio R Banga
Motivation: Optimality principles have been used to explain many biological processes and systems. However, the functions being optimized are in general unknown a priori. Here we present an inverse optimal control (IOC) framework for modeling dynamics in systems biology. The objective is to identify the underlying optimality principle from observed time-series data and simultaneously estimate unmeasured time-dependent inputs and time-invariant model parameters. As a special case, we also consider the problem of optimal simultaneous estimation of inputs and parameters from noisy data...
March 7, 2018: Bioinformatics
Saeideh Jalali, Amir Zarrinhaghighi, Saman Sadraei, Younes Ghasemi, Amirhossein Sakhteman, Pouya Faridi
Background The plant Nardostachys jatamansi from Valerianaceae family is a well known antidepressant plant and has historically been used in traditional medicine. As N. jatamansi contains many different compounds, to identify its mechanisms of action, we need a network-based study. Network-based studies are becoming an increasingly important tool in understanding the mechanisms of actions of drugs. Systems pharmacology (SP) and bioinformatics are two emerging tools that use computation to develop an understanding of drug actions in molecular and cellular levels...
March 5, 2018: Current Drug Metabolism
B K B Lee, C P Gan, J K Chang, J L Tan, M Z Fadlullah, Z A Abdul Rahman, S S Prime, J S Gutkind, C S Liew, T F Khang, A C Tan, S C Cheong
Head and neck cancer (HNC)-derived cell lines represent fundamental models for studying the biological mechanisms underlying cancer development and precision therapies. However, mining the genomic information of HNC cells from available databases requires knowledge on bioinformatics and computational skill sets. Here, we developed a user-friendly web resource for exploring, visualizing, and analyzing genomics information of commonly used HNC cell lines. We populated the current version of GENIPAC with 44 HNC cell lines from 3 studies: ORL Series, OPC-22, and H Series...
March 1, 2018: Journal of Dental Research
Kirill Veselkov, Jonathan Sleeman, Emmanuelle Claude, Johannes P C Vissers, Dieter Galea, Anna Mroz, Ivan Laponogov, Mark Towers, Robert Tonge, Reza Mirnezami, Zoltan Takats, Jeremy K Nicholson, James I Langridge
Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets...
March 6, 2018: Scientific Reports
Kun-Hsing Yu, Tsung-Lu Lee, Chi-Shiang Wang, Yu-Ju Chen, Christopher Ré, Samuel C Kou, Jung-Hsien Chiang, Isaac S Kohane, Michael Snyder
There are more than 3.7 million published articles on the biological functions or disease implications of proteins, constituting an important resource of proteomics knowledge. However, it is difficult to summarize the millions of proteomics findings in the literature manually and quantify their relevance to the biology and diseases of interest. In this study, we developed a fully-automated bioinformatics framework to identify and prioritize proteins associated with any biological entity. We used the 22 targeted areas of the Biology/Disease-driven (B/D)-Human Proteome Project (HPP) as examples, prioritized the relevant proteins through their Protein Universal Reference Publication-Originated Search Engine (PURPOSE) scores, validated the relevance of the score by comparing the protein prioritization results with a curated database, computed the scores of proteins across the topics of B/D-HPP, and characterized the top proteins in the common model organisms...
March 5, 2018: Journal of Proteome Research
Jan K Szymański, Yousef M Abul-Haija, Leroy Cronin
Millions of years of biological evolution have driven the development of highly sophisticated molecular machinery found within living systems. These systems produce polymers such as proteins and nucleic acids with incredible fidelity and function. In nature, the precise molecular sequence is the factor that determines the function of these macromolecules. Given that the ability to precisely define sequence emerges naturally, the fact that biology achieves unprecedented control over the unit sequence of the monomers through evolved enzymatic catalysis is incredible...
March 1, 2018: Accounts of Chemical Research
Muhammad Tahir, Bismillah Jan, Maqsood Hayat, Shakir Ullah Shah, Muhammad Amin
BACKGROUND AND OBJECTIVE: Discriminative and informative feature extraction is the core requirement for accurate and efficient classification of protein subcellular localization images so that drug development could be more effective. The objective of this paper is to propose a novel modification in the Threshold Adjacency Statistics technique and enhance its discriminative power. METHODS: In this work, we utilized Threshold Adjacency Statistics from a novel perspective to enhance its discrimination power and efficiency...
April 2018: Computer Methods and Programs in Biomedicine
Oluwatosin Oluwadare, Yuxiang Zhang, Jianlin Cheng
BACKGROUND: The development of chromosomal conformation capture techniques, particularly, the Hi-C technique, has made the analysis and study of the spatial conformation of a genome an important topic in bioinformatics and computational biology. Aided by high-throughput next generation sequencing techniques, the Hi-C technique can generate genome-wide, large-scale intra- and inter-chromosomal interaction data capable of describing in details the spatial interactions within a genome. These data can be used to reconstruct 3D structures of chromosomes that can be used to study DNA replication, gene regulation, genome interaction, genome folding, and genome function...
February 23, 2018: BMC Genomics
Nagore Cuevas, Marta Martins, Pedro M Costa
Estuaries, coastal lagoons and other transition ecosystems tend to become the ultimate reservoirs of pollutants transported by continental runoff, among which pesticides constitute the class of most concern. High amounts of dissolved and particulated organic matter greatly contribute to the accumulation of pesticides that eventually become trapped in sediments or find their way along food chains. Perhaps not so surprisingly, it is common to find elevated levels of pesticides in estuarine sediments decades after their embargo...
February 15, 2018: Ecotoxicology
Ivan Laponogov, Noureddin Sadawi, Dieter Galea, Reza Mirnezami, Kirill A Veselkov, Jonathan Wren
Motivation: High-resolution mass spectrometry permits simultaneous detection of thousands of different metabolites in biological samples; however their automated annotation still presents a challenge due to the limited number of tailored computational solutions freely available to the scientific community. Results: Here we introduce ChemDistiller, a customizable engine that combines automated large-scale annotation of metabolites using tandem MS data with a compiled database containing tens of millions of compounds with pre-calculated 'fingerprints' and fragmentation patterns...
February 12, 2018: Bioinformatics
Nidia Obscura Acosta, Veli Mäkinen, Alexandru I Tomescu
Background: Reconstructing the genome of a species from short fragments is one of the oldest bioinformatics problems. Metagenomic assembly is a variant of the problem asking to reconstruct the circular genomes of all bacterial species present in a sequencing sample. This problem can be naturally formulated as finding a collection of circular walks of a directed graph G that together cover all nodes, or edges, of G . Approach: We address this problem with the "safe and complete" framework of Tomescu and Medvedev (Research in computational Molecular biology-20th annual conference, RECOMB 9649:152-163, 2016)...
2018: Algorithms for Molecular Biology: AMB
Nathan Mih, Elizabeth Brunk, Ke Chen, Edward Catoiu, Anand Sastry, Erol Kavvas, Jonathan M Monk, Zhen Zhang, Bernhard O Palsson, Alfonso Valencia
Summary: Working with protein structures at the genome-scale has been challenging in a variety of ways. Here, we present ssbio, a Python package that provides a framework to easily work with structural information in the context of genome-scale network reconstructions, which can contain thousands of individual proteins. The ssbio package provides an automated pipeline to construct high quality genomescale models with protein structures (GEM-PROs), wrappers to popular third-party programs to compute associated protein properties, and methods to visualize and annotate structures directly in Jupyter notebooks, thus lowering the barrier of linking 3D structural data with established systems workflows...
February 12, 2018: Bioinformatics
Andrew C Doxey, Michael J Mansfield, Cesare Montecucco
Hundreds and hundreds of bacterial protein toxins are presently known. Traditionally, toxin identification begins with pathological studies of bacterial infectious disease. Following identification and cultivation of a bacterial pathogen, the protein toxin is purified from the culture medium and its pathogenic activity is studied using the methods of biochemistry and structural biology, cell biology, tissue and organ biology, and appropriate animal models, supplemented by bioimaging techniques. The ongoing and explosive development of high-throughput DNA sequencing and bioinformatic approaches have set in motion a revolution in many fields of biology, including microbiology...
February 10, 2018: Toxicon: Official Journal of the International Society on Toxinology
Guillaume Noell, Rosa Faner, Alvar Agustí
Human health and disease are emergent properties of a complex, nonlinear, dynamic multilevel biological system: the human body. Systems biology is a comprehensive research strategy that has the potential to understand these emergent properties holistically. It stems from advancements in medical diagnostics, "omics" data and bioinformatic computing power. It paves the way forward towards "P4 medicine" (predictive, preventive, personalised and participatory), which seeks to better intervene preventively to preserve health or therapeutically to cure diseases...
March 31, 2018: European Respiratory Review: An Official Journal of the European Respiratory Society
Deborah R Winter
High-throughput sequencing assays have become an increasingly common part of biological research across multiple fields. Even as the resulting sequences pile up in public databases, it is not always obvious how to make use of these data sets. Functional genomics offers approaches to integrate these "big" data into our understanding of rheumatic diseases. This review aims to provide a primer on thinking about big data from functional genomics in the context of rheumatology, using examples from the field's literature as well as the author's own work to illustrate the execution of functional genomics research...
February 12, 2018: Arthritis Research & Therapy
P Popov, S Grudinin
Conformational ensembles comprise one of the fundamental concepts in statistical bioinformatics and appear in a variety of applications, e.g. molecular docking, virtual screening, searching for pharmacophores, etc. High-throughput applications require billions of conformations to be considered, thus, one often uses the rigid-body representation of molecules or its fragments to cope with the computational cost. Of particular interest is generation of the near-native conformational ensembles, which consist of conformations structurally close to the biologically relevant ones...
February 2, 2018: Journal of Molecular Graphics & Modelling
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