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

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https://www.readbyqxmd.com/read/30004242/scalable-consistency-in-t-coffee-through-apache-spark-and-cassandra-database
#1
Jordi Lladós, Fernando Cores, Fernando Guirado
Next-generation sequencing, also known as high-throughput sequencing, has increased the volume of genetic data processed by sequencers. In the bioinformatic scientific area, highly rated multiple sequence alignment tools, such as MAFFT, ProbCons, and T-Coffee (TC), use the probabilistic consistency as a prior step to the progressive alignment stage to improve the final accuracy. However, such methods are severely limited by the memory required to store the consistency information. Big data processing and persistence techniques are used to manage and store the huge amount of information that is generated...
July 13, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30004240/massively-parallel-implementation-of-sequence-alignment-with-basic-local-alignment-search-tool-using-parallel-computing-in-java-library
#2
Marek Nowicki, Davit Bzhalava, Piotr BaŁa
Basic Local Alignment Search Tool (BLAST) is an essential algorithm that researchers use for sequence alignment analysis. The National Center for Biotechnology Information (NCBI)-BLAST application is the most popular implementation of the BLAST algorithm. It can run on a single multithreading node. However, the volume of nucleotide and protein data is fast growing, making single node insufficient. It is more and more important to develop high-performance computing solutions, which could help researchers to analyze genetic data in a fast and scalable way...
July 13, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29993281/mixprotool-a-powerful-and-comprehensive-web-tool-for-analyzing-and-visualizing-multigroup-proteomics-data
#3
Shisheng Wang, Wen Zheng, Liqiang Hu, Meng Gong, Hao Yang
Deciphering and visualizing proteomics data are a big challenge for high-throughput proteomics research. In this work, we develop a free interactive web software platform, MixProTool, for processing multigroup proteomics data sets. This tool provides integrated data analysis workflow, including quality control assessment, normalization, soft independent modeling of class analogy, statistics, gene ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. This software is also highly compatible with the identification and quantification results of various frequently used search engines, such as MaxQuant, Proteome Discoverer, or Mascot...
July 11, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29993269/parallel-tiled-codes-implementing-the-smith-waterman-alignment-algorithm-for-two-and-three-sequences
#4
Marek Palkowski, Wlodzimierz Bielecki
The Smith-Waterman (SW) algorithm explores all the possible alignments between two or more sequences and as a result it returns the optimal local alignment. However, the computational cost of this algorithm is very high, and the exponential growth of computation makes SW unrealistic for searching similarities in large sets of sequences. Fortunately, the dynamic programming kernel of the SW algorithm involves mathematical operations over affine control loops whose iteration space can be represented by the polyhedral model...
July 11, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29993261/strong-weak-feature-recognition-of-promoters-based-on-position-weight-matrix-and-ensemble-set-valued-models
#5
Qie Liu, Min Liu, Wenfa Wu
In this article, we propose a method to recognize the strong/weak property of the promoters based on the nucleotide sequence. To the best of our knowledge, it is the first time to predict the strong/weak property of the promoters. First, position weight matrix (PWM) is used to evaluate the contributions of the nucleotides to the promoter strength. Then, the set-valued model is used to describe the relation between the nucleotide sequence and the strength. Considering the small-sample and imbalance features of the promoter data, we propose an ensemble approach to predict the strong/weak property of the promoters...
July 11, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29985650/large-scale-simulations-of-bacterial-populations-over-complex-networks
#6
Andreia Sofia Teixeira, Pedro T Monteiro, João A Carriço, Francisco C Santos, Alexandre P Francisco
The understanding of bacterial population genetics and evolution is crucial in epidemic outbreak studies and pathogen surveillance. However, all epidemiological studies are limited to their sampling capacities which, by being usually biased or limited due to economic constraints, can hamper the real knowledge of the bacterial population structure of a given species. To this end, mathematical models and large-scale simulations can provide a quantitative analytical framework that can be used to assess how or if limited sampling can infer the true population structure...
July 9, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29963923/detecting-periodicities-in-eukaryotic-genomes-by-ramanujan-fourier-transform
#7
Jian Zhao, Jiasong Wang, Hongmei Jiang
Ramanujan Fourier transform (RFT) nowadays is becoming a popular signal processing method. RFT is used to detect periodicities in exons and introns of eukaryotic genomes in this article. Genomic sequences of nine species were analyzed. The highest peak in the spectrum amplitude corresponding to each exon or intron is regarded as the significant signal. Accordingly, the periodicity corresponding to the significant signal can be also regarded as a valuable periodicity. Exons and introns have different periodic phenomena...
July 2, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29963911/prediction-of-rare-palmitoylation-events-in-proteins
#8
Bandana Kumari, Ravindra Kumar, Manish Kumar
Palmitoylation directs many cellular processes such as protein trafficking, sorting, signaling, interactions with other biomolecules, to name a few. Palmitoylation commonly occurs on cysteine; however, occasional palmitoylation of few other amino acids has also been reported. To date, comprehensive analysis on occasional palmitoylation is unavailable. In the present study, we reported a computational method to predict palmitoylation of glycine and serine residues in a protein. The method is based on support vector machine (SVM)...
July 2, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29963900/a-novel-method-for-assessing-the-statistical-significance-of-rna-rna-interactions-between-two-long-rnas
#9
Tsukasa Fukunaga, Michiaki Hamada
RNA-RNA interactions are key mechanisms through which noncoding RNA (ncRNA) regions exert biological functions. Computational prediction of RNA-RNA interactions is an essential method for detecting novel RNA-RNA interactions because their comprehensive detection by biological experimentation is still quite difficult. Many RNA-RNA interaction prediction tools have been developed, but they tend to produce many false positives. Accordingly, assessment of the statistical significance of computationally predicted interactions is an important task...
July 2, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29957033/signature-gene-identification-of-cancer-occurrence-and-pattern-recognition
#10
Jian-Xin Wen, Xiao-Qin Li, Yu Chang
To identify signature genes for the pathogenesis of cancer, which provides a theoretical support for prevention and early diagnosis of cancer. The pattern recognition method was used to analyze the genome-wide gene expression data, which was collected from the The Cancer Genome Atlas (TCGA) database. For the transcription of invasive breast carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, colon adenocarcinoma, renal clear-cell carcinoma, thyroid carcinoma, and hepatocellular carcinoma of the seven cancers, the signature genes were selected by means of a combination of statistical methods, such as correlation, t-test, confidence interval, etc...
June 29, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29957032/a-power-performance-perspective-to-multiobjective-electroencephalogram-feature-selection-on-heterogeneous-parallel-platforms
#11
Juan José Escobar, Julio Ortega, Antonio Francisco Díaz, Jesús González, Miguel Damas
This article provides an insight on the power-performance issues related with the CPU-GPU (Central Processing Unit-Graphics Processing Unit) parallel implementations of problems that frequently appear in the context of applications on bioinformatics and biomedical engineering. More specifically, we analyze the power-performance behavior of an evolutionary parallel multiobjective electroencephalogram feature selection procedure that evolves subpopulations of solutions with time-demanding fitness evaluation. The procedure has been implemented in OpenMP to dynamically distribute either subpopulations or individuals among devices, and uses OpenCL to evaluate the fitness of the individuals...
June 29, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29957031/determining-the-transcription-rates-yielding-steady-state-production-of-mrna-in-the-lac-genetic-switch-of-escherichia-coli
#12
Komlan Atitey, Pavel Loskot, Paul Rees
To elucidate the regulatory dynamics of the gene expression activation and inactivation, an in silico biochemical model of the lac circuit in Escherichia coli was used to evaluate the transcription rates that yield the steady-state mRNA production in active and inactive states of the lac circuit. This result can be used in synthetic biology applications to understand the limits of the genetic synthesis. Since most genetic networks involve many interconnected components with positive and negative feedback control, intuitive understanding of their dynamics is often difficult to obtain...
June 29, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29932739/using-stochastic-approximation-techniques-to-efficiently-construct-confidence-intervals-for-heritability
#13
Regev Schweiger, Eyal Fisher, Elior Rahmani, Liat Shenhav, Saharon Rosset, Eran Halperin
Estimation of heritability is an important task in genetics. The use of linear mixed models (LMMs) to determine narrow-sense single-nucleotide polymorphism (SNP)-heritability and related quantities has received much recent attention, due of its ability to account for variants with small effect sizes. Typically, heritability estimation under LMMs uses the restricted maximum likelihood (REML) approach. The common way to report the uncertainty in REML estimation uses standard errors (SEs), which rely on asymptotic properties...
June 22, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29932737/improving-single-nucleotide-polymorphism-based-fetal-fraction-estimation-of-maternal-plasma-circulating-cell-free-dna-using-bayesian-hierarchical-models
#14
Nicholas B Larson, Chen Wang, Jie Na, Ross A Rowsey, William Edward Highsmith, Nicole L Hoppman, Jean-Pierre Kocher, Eric W Klee
The recent advances in next-generation sequencing (NGS) technologies have enabled the development of effective high-throughput noninvasive prenatal screening (NIPS) assays for fetal genetic abnormalities using maternal circulating cell-free DNA (ccfDNA). An important NIPS quality assurance is quantifying the fetal proportion of the sampled ccfDNA. For methods using allelic read count ratios from targeted sequencing of single-nucleotide polymorphisms (SNPs), systematic biases and errors may reduce accuracy and diminish assay performance...
June 22, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29927624/applying-a-modified-wavelet-shrinkage-filter-to-improve-cryo-electron-microscopy-imaging
#15
Xinrui Huang, Sha Li, Song Gao
Cryo-electron microscopy (Cryo-EM) imaging has the unique potential to bridge the gap between cellular and molecular biology by revealing the structures of large macromolecular assemblies and cellular complexes. Therefore, cryo-EM three-dimensional (3D) reconstruction has been rapidly developed in recent several years and applied widely in life science research; however, it suffers from reduced contrast and low signal-to-noise ratios with a high degree of noise under low electron dose conditions, resulting in failures of many conventional filters...
June 21, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29927616/simulation-model-of-bacterial-resistance-to-antibiotics-using-individual-based-modeling
#16
Joonyeon Park, Myeongji Cho, Hyeon S Son
We designed and implemented simulation models of bacterial growth and antibiotic resistance to determine the appropriate antibiotics to use against antibiotic-resistant bacteria. Simulation models were designed using individual-based modeling, and a simulation tool, ARSim, was developed to conduct experiments using the models. Simulations of bacterial growth were conducted by virtually growing Klebsiella pneumoniae bacteria in a virtual environment with predefined parameters. Other experiments included predicting the effects of antibiotics when added to two different groups, one group of nonresistant bacteria and another group of both resistant and nonresistant bacteria...
June 21, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29927613/a-bayesian-active-learning-experimental-design-for-inferring-signaling-networks
#17
Robert O Ness, Karen Sachs, Parag Mallick, Olga Vitek
Machine learning methods for learning network structure are applied to quantitative proteomics experiments and reverse-engineer intracellular signal transduction networks. They provide insight into the rewiring of signaling within the context of a disease or a phenotype. To learn the causal patterns of influence between proteins in the network, the methods require experiments that include targeted interventions that fix the activity of specific proteins. However, the interventions are costly and add experimental complexity...
June 21, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29905491/estimation-of-dynamic-systems-for-gene-regulatory-networks-from-dependent-time-course-data
#18
Yoonji Kim, Jaejik Kim
Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models...
June 15, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29889553/adaptive-local-realignment-of-protein-sequences
#19
Dan DeBlasio, John Kececioglu
While mutation rates can vary markedly over the residues of a protein, multiple sequence alignment tools typically use the same values for their scoring-function parameters across a protein's entire length. We present a new approach, called adaptive local realignment, that in contrast automatically adapts to the diversity of mutation rates along protein sequences. This builds upon a recent technique known as parameter advising, which finds global parameter settings for an aligner, to now adaptively find local settings...
June 11, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29792514/a-flow-procedure-for-linearization-of-genome-sequence-graphs
#20
David Haussler, Maciej Smuga-Otto, Jordan M Eizenga, Benedict Paten, Adam M Novak, Sergei Nikitin, Maria Zueva, Dmitrii Miagkov
Efforts to incorporate human genetic variation into the reference human genome have converged on the idea of a graph representation of genetic variation within a species, a genome sequence graph. A sequence graph represents a set of individual haploid reference genomes as paths in a single graph. When that set of reference genomes is sufficiently diverse, the sequence graph implicitly contains all frequent human genetic variations, including translocations, inversions, deletions, and insertions. In representing a set of genomes as a sequence graph, one encounters certain challenges...
May 24, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
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