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Journal of Computational Biology: a Journal of Computational Molecular Cell Biology

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https://www.readbyqxmd.com/read/28715269/fsg-fast-string-graph-construction-for-de-novo-assembly
#1
Paola Bonizzoni, Gianluca Della Vedova, Yuri Pirola, Marco Previtali, Raffaella Rizzi
The string graph for a collection of next-generation reads is a lossless data representation that is fundamental for de novo assemblers based on the overlap-layout-consensus paradigm. In this article, we explore a novel approach to compute the string graph, based on the FM-index and Burrows and Wheeler Transform. We describe a simple algorithm that uses only the FM-index representation of the collection of reads to construct the string graph, without accessing the input reads. Our algorithm has been integrated into the string graph assembler (SGA) as a standalone module to construct the string graph...
July 17, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28715235/cutprimers-a-new-tool-for-accurate-cutting-of-primers-from-reads-of-targeted-next-generation-sequencing
#2
Andrey Kechin, Uljana Boyarskikh, Alexander Kel, Maxim Filipenko
Cutting of primers from reads is an important step of processing targeted amplicon-based next generation sequencing data. Existing tools are adapted for cutting of one or several primer/adapter sequences from reads and removing all of their occurrences. Also most of the existing tools use kmers and may cut only part of primers or primers with studied sequence of gene. Because of this, use of such programs leads to incorrect trimming, reduction of coverage, and increase in the number of false-positive and/or false-negative results...
July 17, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28686467/diagnosis-prediction-from-electronic-health-records-using-the-binary-diagnosis-history-vector-representation
#3
Ieva Vasiljeva, Ognjen Arandjelović
Large amounts of rich, heterogeneous information nowadays routinely collected by healthcare providers across the world possess remarkable potential for the extraction of novel medical data and the assessment of different practices in real-world conditions. Specifically in this work, our goal is to use electronic health records (EHRs) to predict progression patterns of future diagnoses of ailments for a particular patient, given the patient's present diagnostic history. Following the highly promising results of a recently proposed approach that introduced the diagnosis history vector representation of a patient's diagnostic record, we introduce a series of improvements to the model and conduct thorough experiments that demonstrate its scalability, accuracy, and practicability in the clinical context...
July 7, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28686466/reducing-alignment-time-complexity-of-ultra-large-sets-of-sequences
#4
Álvaro Rubio-Largo, Leonardo Vanneschi, Mauro Castelli, Miguel A Vega-Rodríguez
The alignment of three or more protein or nucleotide sequences is known as Multiple Sequence Alignment problem. The complexity of this problem increases exponentially with the number of sequences; therefore, many of the current approaches published in the literature suffer a computational overhead when thousands of sequences are required to be aligned. We introduce a new approach for dealing with ultra-large sets of sequences. A two-level clustering method is considered. The first level clusters the input sequences by using their biological composition, that is, the number of positive, negative, polar, special, and hydrophobic amino acids...
July 7, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28686463/evolution-and-vaccination-of-influenza-virus
#5
Ham Ching Lam, Xuan Bi, Srinand Sreevatsan, Daniel Boley
In this study, we present an application paradigm in which an unsupervised machine learning approach is applied to the high-dimensional influenza genetic sequences to investigate whether vaccine is a driving force to the evolution of influenza virus. We first used a visualization approach to visualize the evolutionary paths of vaccine-controlled and non-vaccine-controlled influenza viruses in a low-dimensional space. We then quantified the evolutionary differences between their evolutionary trajectories through the use of within- and between-scatter matrices computation to provide the statistical confidence to support the visualization results...
July 7, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28686462/a-logic-for-checking-the-probabilistic-steady-state-properties-of-reaction-networks
#6
Vincent Picard, Anne Siegel, Jérémie Bourdon
Designing probabilistic reaction models and determining their stochastic kinetic parameters are major issues in systems biology. To assist in the construction of reaction network models, we introduce a logic that allows one to express asymptotic properties about the steady-state stochastic dynamics of a reaction network. Basically, the formulas can express properties on expectancies, variances, and covariances. If a formula encoding for experimental observations on the system is not satisfiable, then the reaction network model can be rejected...
July 7, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28682641/psuc-pserat-predicting-lysine-succinylation-in-proteins-by-exploiting-the-ratios-of-sequence-coupling-and-properties
#7
Haixin Ai, Runlin Wu, Li Zhang, Xuewei Wu, Junchao Ma, Huan Hu, Liangchao Huang, Wen Chen, Jian Zhao, Hongsheng Liu
Lysine succinylation is an extremely important protein post-translational modification that plays a fundamental role in regulating various biological reactions, and dysfunction of this process is associated with a number of diseases. Thus, determining which Lys residues in an uncharacterized protein sequence are succinylated underpins both basic research and drug development endeavors. To solve this problem, we have developed a predictor called pSuc-PseRat. The features of the pSuc-PseRat predictor are derived from two aspects: (1) the binary encoding from succinylated sites and non-succinylated sites; (2) the sequence-coupling effects between succinylated sites and non-succinylated sites...
July 6, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28682119/application-of-time-frequency-domain-transform-to-three-dimensional-interpolation-of-medical-images
#8
Shengqing Lv, Yimin Chen, Zeyu Li, Jiahui Lu, Mingke Gao, Rongrong Lu
Medical image three-dimensional (3D) interpolation is an important means to improve the image effect in 3D reconstruction. In image processing, the time-frequency domain transform is an efficient method. In this article, several time-frequency domain transform methods are applied and compared in 3D interpolation. And a Sobel edge detection and 3D matching interpolation method based on wavelet transform is proposed. We combine wavelet transform, traditional matching interpolation methods, and Sobel edge detection together in our algorithm...
July 6, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28650678/an-integrative-approach-for-identifying-network-biomarkers-of-breast-cancer-subtypes-using-genomic-interactomic-and-transcriptomic-data
#9
Forough Firoozbakht, Iman Rezaeian, Michele D'agnillo, Lisa Porter, Luis Rueda, Alioune Ngom
Breast cancer is a complex disease that can be classified into at least 10 different molecular subtypes. Appropriate diagnosis of specific subtypes is critical for ensuring the best possible patient treatment and response to therapy. Current computational methods for determining the subtypes are based on identifying differentially expressed genes (i.e., biomarkers) that can best discriminate the subtypes. Such approaches, however, are known to be unreliable since they yield different biomarker sets when applied to data sets from different studies...
June 26, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28636461/genice-a-novel-framework-for-gene-network-inference-by-clustering-exhaustive-search-and-multivariate-analysis
#10
Ricardo de Souza Jacomini, David Correa Martins-Jr, Felipe Leno da Silva, Anna Helena Reali Costa
Gene network (GN) inference from temporal gene expression data is a crucial and challenging problem in systems biology. Expression data sets usually consist of dozens of temporal samples, while networks consist of thousands of genes, thus rendering many inference methods unfeasible in practice. To improve the scalability of GN inference methods, we propose a novel framework called GeNICE, based on probabilistic GNs; the main novelty is the introduction of a clustering procedure to group genes with related expression profiles and to provide an approximate solution with reduced computational complexity...
June 21, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28632436/development-of-computer-algorithm-for-editing-of-next-generation-sequencing-metagenome-data
#11
Radhika Khanna, Sangeeta Mittal, Sujata Mohanty
The successful implementation of the advanced sequencing technology, the next generation sequencing (NGS) motivates scientists from diverse fields of biological research especially from genomics and transcriptomics in generating large genomic data set to make their analysis more robust and come up with strong inference. However, exploiting this huge genomic data set becomes a challenge for the molecular biologists. To corroborate this problem, computational software and hardware are being developed in parallel and become an integral part of life science...
June 20, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28632429/on-stable-states-in-a-topologically-driven-protein-folding-model
#12
Zheng Dai, David Becerra, Jérôme Waldispühl
Theoretical models of protein folding often make simplifying assumptions that allow analysis, yielding interesting theoretical results. In this article, we study models where folding dynamics is primarily driven by local topological features in an iterative manner. We illustrate the merit of the proposed approach through its ability to simulate realistic protein folding processes even when the sequence content information is reduced to just hydrophobic and polar. We then analyze our models and show that under our simple assumptions, certain structures are inherently unstable, and that determining whether structures can be stable is an [Formula: see text]-hard problem...
June 20, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28632401/motifsim-2-1-an-enhanced-software-platform-for-detecting-similarity-in-multiple-dna-motif-data-sets
#13
Ngoc Tam L Tran, Chun-Hsi Huang
Finding binding site motifs plays an important role in bioinformatics as it reveals the transcription factors that control the gene expression. The development for motif finders has flourished in the past years with many tools have been introduced to the research community. Although these tools possess exceptional features for detecting motifs, they report different results for an identical data set. Hence, using multiple tools is recommended because motifs reported by several tools are likely biologically significant...
June 20, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28632399/prokaryotic-contig-annotation-pipeline-server-web-application-for-a-prokaryotic-genome-annotation-pipeline-based-on-the-shiny-app-package
#14
Byeonghyeok Park, Min-Jeong Baek, Byoungnam Min, In-Geol Choi
Genome annotation is a primary step in genomic research. To establish a light and portable prokaryotic genome annotation pipeline for use in individual laboratories, we developed a Shiny app package designated as "P-CAPS" (Prokaryotic Contig Annotation Pipeline Server). The package is composed of R and Python scripts that integrate publicly available annotation programs into a server application. P-CAPS is not only a browser-based interactive application but also a distributable Shiny app package that can be installed on any personal computer...
June 20, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28632398/the-mitochondrial-protein-atlas-a-database-of-experimentally-verified-information-on-the-human-mitochondrial-proteome
#15
Noa Godin, Jerry Eichler
Given its central role in various biological systems, as well as its involvement in numerous pathologies, the mitochondrion is one of the best-studied organelles. However, although the mitochondrial genome has been extensively investigated, protein-level information remains partial, and in many cases, hypothetical. The Mitochondrial Protein Atlas (MPA; URL: lifeserv.bgu.ac.il/wb/jeichler/MPA ) is a database that provides a complete, manually curated inventory of only experimentally validated human mitochondrial proteins...
June 20, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28581814/hybrid-statistical-and-mechanistic-mathematical-model-guides-mobile-health-intervention-for-chronic-pain
#16
Sara M Clifton, Chaeryon Kang, Jingyi Jessica Li, Qi Long, Nirmish Shah, Daniel M Abrams
Nearly a quarter of visits to the emergency department are for conditions that could have been managed via outpatient treatment; improvements that allow patients to quickly recognize and receive appropriate treatment are crucial. The growing popularity of mobile technology creates new opportunities for real-time adaptive medical intervention, and the simultaneous growth of "big data" sources allows for preparation of personalized recommendations. Here we focus on the reduction of chronic suffering in the sickle cell disease (SCD) community...
June 5, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28570142/an-efficient-approach-to-explore-and-discriminate-anomalous-regions-in-bacterial-genomes-based-on-maximum-entropy
#17
Gesiele Almeida Barros-Carvalho, Marie-Anne Van Sluys, Fabricio Martins Lopes
Recently, there has been an increase in the number of whole bacterial genomes sequenced, mainly due to the advancing of next-generation sequencing technologies. In face of this, there is a need to provide new analytical alternatives that can follow this advance. Given our current knowledge about the genomic plasticity of bacteria and that those genomic regions can uncover important features about this microorganism, our goal was to develop a fast methodology based on maximum entropy (ME) to guide the researcher to regions that could be prioritized during the analysis...
June 1, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28570130/an-integrative-computational-approach-to-evaluate-genetic-markers-for-chronic-lymphocytic-leukemia
#18
Yu Zheng, Xiaoyang Li, Lydia C Manor, Hongbao Cao, Qiusheng Chen
Recent studies reported hundreds of genes linked to chronic lymphocytic leukemia (CLL). However, many of these candidate genes were lack of replication and results were not always consistent. Here, we proposed a computational workflow to curate and evaluate CLL-related genes. The method integrates large-scale literature knowledge data, gene expression data, and related pathways/network information for quantitative marker evaluation. Pathway Enrichment, Sub-Network Enrichment, and Gene-Gene Interaction analysis were conducted to study the pathogenic profile of the candidate genes, with four metrics proposed and validated for each gene...
June 1, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28570104/detection-of-complexes-in-biological-networks-through-diversified-dense-subgraph-mining
#19
Xiuli Ma, Guangyu Zhou, Jingbo Shang, Jingjing Wang, Jian Peng, Jiawei Han
Protein-protein interaction (PPI) networks, providing a comprehensive landscape of protein interaction patterns, enable us to explore biological processes and cellular components at multiple resolutions. For a biological process, a number of proteins need to work together to perform a job. Proteins densely interact with each other, forming large molecular machines or cellular building blocks. Identification of such densely interconnected clusters or protein complexes from PPI networks enables us to obtain a better understanding of the hierarchy and organization of biological processes and cellular components...
June 1, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28570103/cavity-versus-ligand-shape-descriptors-application-to-urokinase-binding-pockets
#20
Natacha Cerisier, Leslie Regad, Dhoha Triki, Anne-Claude Camproux, Michel Petitjean
We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA-ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere...
June 1, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
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