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Allan J R Ferrari, Milan A Clasen, Louise Kurt, Paulo C Carvalho, Fabio C Gozzo, Leandro Martínez
Summary: A software was developed to evaluate structural models using chemical crosslinking experiments. The user provides the types of linkers used and their reactivity, and the observed crosslinks and dead-ends. The software computes the minimum length of a physically-inspired linker that connects the reactive atoms of interest, and reports the consistency of each distance with the experimental observation. Statistics on model consistency with the links are provided. Tools to evaluate the correlation of crosslinks in ensembles of models were developed...
January 10, 2019: Bioinformatics
Allan J R Ferrari, Fabio C Gozzo, Leandro Martínez
Motivation: Chemical cross-linking/Mass Spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful...
January 10, 2019: Bioinformatics
Eric J Kort, Stefan Jovinge
Summary: The L1000 data set from the NIH LINCS program holds the promise to deconvolute a wide range of biological questions in transcriptional space. However, using this large and decentralized data set presents its own challenges. The slinky package was created to streamline the process of identifying samples of interest and their corresponding control samples, and loading their associated expression data and metadata. The package can integrate with workflows leveraging the BioConductor collection of tools by encapsulating the L1000 data as a SummarizedExperiment object...
January 10, 2019: Bioinformatics
Chun-Chi Chen, Hyundoo Jeong, Xiaoning Qian, Byung-Jun Yoon
Motivation: For many RNA families, the secondary structure is known to be better conserved among the member RNAs compared to the primary sequence. For this reason, it is important to consider the underlying folding structures when aligning RNA sequences, especially for those with relatively low sequence identity. Given a set of RNAs with unknown structures, simultaneous RNA alignment and folding algorithms aim to accurately align the RNAs by jointly predicting their consensus secondary structure and the optimal sequence alignment...
January 10, 2019: Bioinformatics
Peter M Bourke, Geert van Geest, Roeland E Voorrips, Johannes Jansen, Twan Kranenburg, Arwa Shahin, Richard G F Visser, Paul Arens, Marinus J M Smulders, Chris Maliepaard
No abstract text is available yet for this article.
January 9, 2019: Bioinformatics
Anastasia Gurinovich, Harold Bae, John J Farrell, Stacy L Andersen, Stefano Monti, Annibale Puca, Gil Atzmon, Nir Barzilai, Thomas T Perls, Paola Sebastiani
Motivation: Over the last decade, more diverse populations have been included in genome-wide association studies (GWAS). If a genetic variant has a varying effect on a phenotype in different populations, GWAS applied to a dataset as a whole may not pinpoint such differences. It is especially important to be able to identify population-specific effects of genetic variants in studies that would eventually lead to development of diagnostic tests or drug discovery. Results: In this paper, we propose PopCluster: an algorithm to automatically discover subsets of individuals in which the genetic effects of a variant are statistically different...
January 8, 2019: Bioinformatics
M A Alsamman, S D Ibrahim, Aladdin Hamwieh
Motivation: Fine mapping becomes a routine trial following quantitative trait loci (QTL) mapping studies to shrink the size of genomic segments underlying causal variants. The availability of whole genome sequences can facilitate the development of high marker density and predict gene content in genomic segments of interest. Correlations between genetic and physical positions of these loci require handling of different experimental genetic data types, and ultimately converting them into positioning markers using a routine and efficient tool...
January 8, 2019: Bioinformatics
Wei Chen, Hao Lv, Fulei Nie, Hao Lin
Motivation: DNA N6-methyladenine (6mA) is associated with a wide range of biological processes. Since the distribution of 6mA site in the genome is non-random, accurate identification of 6mA sites is crucial for understanding its biological functions. Although experimental methods have been proposed for this regard, they are still cost-ineffective for detecting 6mA site in genome-wide scope. Therefore, it is desirable to develop computational methods to facilitate the identification of 6mA site...
January 8, 2019: Bioinformatics
Diego A A Morais, Rita M C Almeida, Rodrigo J S Dalmolin
Motivation: Several freely available tools perform analysis using algorithms developed to identify significant variation of gene expression individually. The transcriptogramer R package uses protein-protein interaction to perform differential expression of functionally associated genes. The software assesses expression profile of entire genetic systems and reveals which biological systems are significantly altered in case-control designed transcriptome experiments. Results: R/Bioconductor transcriptogramer package projects expression values on an ordered gene list to perform topological analysis, differential expression, and Gene Ontology enrichment analysis, independently of data platform or operating system...
January 8, 2019: Bioinformatics
Helge Hass, Carolin Loos, Elba Raimundez Alvarez, Jens Timmer, Jan Hasenauer, Clemens Kreutz
Motivation: Dynamic models are used in systems biology to study and understand cellular processes like gene regulation or signal transduction. Frequently, ordinary differential equation (ODE) models are used to model the time and dose dependency of the abundances of molecular compounds as well as interactions and translocations. A multitude of computational approaches, e.g. for parameter estimation or uncertainty analysis have been developed within recent years. However, many of these approaches lack proper testing in application settings because a comprehensive set of benchmark problems is yet missing...
January 8, 2019: Bioinformatics
Jinyan Chan, Xuan Wang, Jacob Turner, Nicole Baldwin, Jinghua Gu
Motivation: Transcriptome-based computational drug repurposing has attracted considerable interest by bringing about faster and more cost-effective drug discovery. Nevertheless, key limitations of the current drug connectivity-mapping paradigm have been long overlooked, including the lack of effective means to determine optimal query gene signatures. Results: The novel approach Dr. Insight implements a frame-breaking statistical model for the "hand-shake" between disease and drug data...
January 8, 2019: Bioinformatics
Blake Hewelt, Haiqing Li, Mohit Kumar Jolly, Prakash Kulkarni, Isa Mambetsariev, Ravi Salgia
Motivation: Advancements in cancer genetics have facilitated the development of therapies with actionable mutations. Although mutated genes have been studied extensively, their chaotic behavior has not been appreciated. Thus, in contrast to naïve DNA, mutated DNA sequences can display characteristics of unpredictability and sensitivity to the initial conditions that may be dictated by the environment, expression patterns, and presence of other genomic alterations. Employing a DNA walk as a form of 2D analysis of the nucleotide sequence, we demonstrate that chaotic behavior in the sequence of a mutated gene can be predicted...
January 7, 2019: Bioinformatics
Paula Tataru, Thomas Bataillon
Summary: Distributions of fitness effects (DFE) of mutations can be inferred from site frequency spectrum (SFS) data. There is mounting interest to determine whether distinct genomic regions and/or species share a common DFE, or whether evidence exists for differences among them. polyDFEv2.0 fits multiple SFS datasets at once and provides likelihood ratio tests for DFE invariance across datasets. Simulations show that testing for DFE invariance across genomic regions within a species requires models accounting for distinct sources of heterogeneity (chance and genuine difference in DFE) underlying differences in SFS data in these regions...
January 7, 2019: Bioinformatics
M Mirdita, M Steinegger, J Söding
Summary: The MMseqs2 desktop and web server app facilitates interactive sequence searches through custom protein sequence and profile databases on personal workstations. By eliminating MMseqs2's runtime overhead, we reduced response times to a few seconds at sensitivities close to BLAST. Availability and implementation: The app is easy to install for non-experts. GPLv3-licensed code, prebuilt desktop app packages for Windows, macOS and Linux, Docker images for the web server application, and a demo web server are available at https://search...
January 7, 2019: Bioinformatics
Houxiang Zhu, Chun Liang
Motivation: The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. Results: In this study, we reanalyzed the published CRISPR-Cpf1 gRNAs data and found many sequence and structural features related to their target efficiency. With the aid of Random Forest in feature selection, a support vector machine (SVM) model was created to predict target efficiency for any given gRNAs...
January 7, 2019: Bioinformatics
L Carron, J B Morlot, V Matthys, A Lesne, J Mozziconacci
Motivation: Genome-wide chromosomal contact maps are widely used to uncover the 3D organisation of genomes. They rely on collecting millions of contacting pairs of genomic loci. Contacts at short range are usually well measured in experiments, while there is a lot of missing information about long-range contacts. Results: We propose to use the sparse information contained in raw contact maps to infer high-confidence contact counts between all pairs of loci. Our algorithmic procedure, Boost-HiC, enables the detection of Hi-C patterns such as chromosomal compartments at a resolution that would be otherwise only attainable by sequencing a hundred times deeper the experimental Hi-C library...
January 4, 2019: Bioinformatics
Georgette Tanner, David R Westhead, Alastair Droop, Lucy F Stead
Summary: Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterise tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this requires sequencing data from appropriately heterogeneous tumours in which the exact trajectory and combination of events occurring throughout its evolution are known...
January 4, 2019: Bioinformatics
Ramzan Umarov, Hiroyuki Kuwahara, Yu Li, Xin Gao, Victor Solovyev
Motivation: Computational identification of promoters is notoriously difficult as human genes often have unique promoter sequences that provide regulation of transcription and interaction with transcription initiation complex. While there are many attempts to develop computational promoter identification methods, we have no reliable tool to analyze long genomic sequences. Results: In this work we further develop our deep learning approach that was relatively successful to discriminate short promoter and non-promoter sequences...
January 2, 2019: Bioinformatics
Jan Ludwiczak, Aleksander Winski, Krzysztof Szczepaniak, Vikram Alva, Stanislaw Dunin-Horkawicz
Motivation: Coiled coils are protein structural domains that mediate a plethora of biological interactions, and thus their reliable annotation is crucial for studies of protein structure and function. Results: Here, we report DeepCoil, a new neural network-based tool for the detection of coiled-coil domains in protein sequences. In our benchmarks, DeepCoil significantly outperformed current state-of-the-art tools, such as PCOILS and Marcoil, both in the prediction of canonical and non-canonical coiled coils...
January 2, 2019: Bioinformatics
Linfang Jin, Jinhuo Lai, Yang Zhang, Ying Fu, Shuhang Wang, Dai Heng, Bingding Huang
Summary: Here we developed a tool called Breakpoint Identification (BreakID) to identity fusion events from targeted sequencing data. Taking discordant read pairs and split reads as supporting evidences, BreakID can identify gene fusion breakpoints at single nucleotide resolution. After validation with confirmed fusion events in cancer cell lines, we have proved that BreakID can achieve high sensitivity of 90.63% along with PPV of 100% at sequencing depth of 500X and perform better than other available fusion detection tools...
January 2, 2019: Bioinformatics
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