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

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https://www.readbyqxmd.com/read/28636461/genice-a-novel-framework-for-gene-network-inference-by-clustering-exhaustive-search-and-multivariate-analysis
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
#7
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
#8
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
#9
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
#10
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
#11
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
https://www.readbyqxmd.com/read/28557607/a-poisson-log-normal-model-for-constructing-gene-covariation-network-using-rna-seq-data
#12
Yoonha Choi, Marc Coram, Jie Peng, Hua Tang
Constructing expression networks using transcriptomic data is an effective approach for studying gene regulation. A popular approach for constructing such a network is based on the Gaussian graphical model (GGM), in which an edge between a pair of genes indicates that the expression levels of these two genes are conditionally dependent, given the expression levels of all other genes. However, GGMs are not appropriate for non-Gaussian data, such as those generated in RNA-seq experiments. We propose a novel statistical framework that maximizes a penalized likelihood, in which the observed count data follow a Poisson log-normal distribution...
May 30, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28541743/rarevar-a-framework-for-detecting-low-frequency-single-nucleotide-variants
#13
Yangyang Hao, Xiaoling Xuei, Lang Li, Harikrishna Nakshatri, Howard J Edenberg, Yunlong Liu
Accurate identification of low-frequency somatic point mutations in tumor samples has important clinical utilities. Although high-throughput sequencing technology enables capturing such variants while sequencing primary tumor samples, our ability for accurate detection is compromised when the variant frequency is close to the sequencer error rate. Most current experimental and bioinformatic strategies target mutations with ≥5% allele frequency, which limits our ability to understand the cancer etiology and tumor evolution...
May 25, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28541721/a-joint-bayesian-model-for-integrating-microarray-and-rna-sequencing-transcriptomic-data
#14
Tianzhou Ma, Faming Liang, Steffi Oesterreich, George C Tseng
As the sequencing cost continued to drop in the past decade, RNA sequencing (RNA-seq) has replaced microarray to become the standard high-throughput experimental tool to analyze transcriptomic profile. As more and more datasets are generated and accumulated in the public domain, meta-analysis to combine multiple transcriptomic studies to increase statistical power has received increasing popularity. In this article, we propose a Bayesian hierarchical model to jointly integrate microarray and RNA-seq studies...
May 25, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28541712/a-comparison-of-two-stage-approaches-based-on-penalized-regression-for-estimating-gene-networks
#15
Minhyeok Lee, Junhee Seok, Donghyun Tae, Hua Zhong, Sung Won Han
Graphical models are commonly used for illustrating gene networks. However, estimating directed networks are generally challenging because of the limited sample size compared with the dimensionality of an experiment. Many previous studies have provided insight into the problem, and recently, two-stage approaches have shown significant improvements for estimating directed acyclic graphs. These two-stage approaches find neighborhoods in the first stage and determine the directions of the edges in the second stage...
May 25, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28489418/studies-on-the-clustering-algorithm-for-analyzing-gene-expression-data-with-a-bidirectional-penalty
#16
Hu Yang, Xiaoqin Liu
This article reports a new clustering method based on the k-means algorithm to high-dimensional gene expression data. The proposed approach makes use of bidirectional penalties to constrain the number of clusters and centroids of clusters to simultaneously determine the unknown number of clusters and handle large amounts of noise in gene expression data. Numeric studies indicate that this algorithm not only performs better in clustering but is also comparable to other approaches in its ability to obtain the correct number of clusters and correct signal features...
May 10, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28489411/gcoda-conditional-dependence-network-inference-for-compositional-data
#17
Huaying Fang, Chengcheng Huang, Hongyu Zhao, Minghua Deng
The increasing quality and the reducing cost of high-throughput sequencing technologies for 16S rRNA gene profiling enable researchers to directly analyze microbe communities in natural environments. The direct interactions among microbial species of a given ecological system can help us understand the principles of community assembly and maintenance under various conditions. Compositionality and dimensionality of microbiome data are two main challenges for inferring the direct interaction network of microbes...
May 10, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28437136/enumeration-of-ancestral-configurations-for-matching-gene-trees-and-species-trees
#18
Filippo Disanto, Noah A Rosenberg
Given a gene tree and a species tree, ancestral configurations represent the combinatorially distinct sets of gene lineages that can reach a given node of the species tree. They have been introduced as a data structure for use in the recursive computation of the conditional probability under the multispecies coalescent model of a gene tree topology given a species tree, the cost of this computation being affected by the number of ancestral configurations of the gene tree in the species tree. For matching gene trees and species trees, we obtain enumerative results on ancestral configurations...
April 24, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28418726/u50-a-new-metric-for-measuring-assembly-output-based-on-non-overlapping-target-specific-contigs
#19
Christina J Castro, Terry Fei Fan Ng
Advances in next-generation sequencing technologies enable routine genome sequencing, generating millions of short reads. A crucial step for full genome analysis is the de novo assembly, and currently, performance of different assembly methods is measured by a metric called N50. However, the N50 value can produce skewed, inaccurate results when complex data are analyzed, especially for viral and microbial datasets. To provide a better assessment of assembly output, we developed a new metric called U50. The U50 identifies unique, target-specific contigs by using a reference genome as baseline, aiming at circumventing some limitations that are inherent to the N50 metric...
April 18, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28414553/gd-rda-a-new-regularized-discriminant-analysis-for-high-dimensional-data
#20
Yan Zhou, Baoxue Zhang, Gaorong Li, Tiejun Tong, Xiang Wan
High-throughput techniques bring novel tools and also statistical challenges to genomic research. Identification of which type of diseases a new patient belongs to has been recognized as an important problem. For high-dimensional small sample size data, the classical discriminant methods suffer from the singularity problem and are, therefore, no longer applicable in practice. In this article, we propose a geometric diagonalization method for the regularized discriminant analysis. We then consider a bias correction to further improve the proposed method...
April 17, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
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