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

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https://www.readbyqxmd.com/read/30422680/a-new-quartet-based-statistical-method-for-comparing-sets-of-gene-trees-is-developed-using-a-generalized-hoeffding-inequality
#1
Eliran Avni, Sagi Snir
Extracting the strength of the tree signal that is encompassed by a collection of gene trees is an exceptionally challenging problem in phylogenomics. Often, this problem not only involves the construction of individual phylogenies based on different genes, which may be a difficult endeavor on its own, but is also exacerbated by many factors that create conflicts between the evolutionary histories of different gene families, such as duplications or losses of genes; hybridization events; incomplete lineage sorting; and horizontal gene transfer, the latter two play central roles in the evolution of eukaryotes and prokaryotes, respectively...
November 13, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30418034/mcat-motif-combining-and-association-tool
#2
Yanshen Yang, Jeffrey A Robertson, Zhen Guo, Jake Martinez, Christy Coghlan, Lenwood S Heath
De novo motif discovery in biological sequences is an important and computationally challenging problem. A myriad of algorithms have been developed to solve this problem with varying success, but it can be difficult for even a small number of these tools to reach a consensus. Because individual tools can be better suited for specific scenarios, an ensemble tool that combines the results of many algorithms can yield a more confident and complete result. We present a novel and fast tool ensemble MCAT (Motif Combining and Association Tool) for de novo motif discovery by combining six state-of-the-art motif discovery tools (MEME, BioProspector, DECOD, XXmotif, Weeder, and CMF)...
November 10, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30383444/small-world-networks-and-rna-secondary-structures
#3
Defne Surujon, Yann Ponty, Peter Clote
Let [Formula: see text] denote the network of all RNA secondary structures of length n, in which undirected edges exist between structures s, t such that t is obtained from s by the addition, removal, or shift of a single base pair. Using context-free grammars, generating functions, and complex analysis, we show that the asymptotic average degree is [Formula: see text], and that the asymptotic clustering coefficient is [Formula: see text], from which it follows that the family [Formula: see text], [Formula: see text] of secondary structure networks is not small world...
October 31, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30383443/word-and-sentence-embedding-tools-to-measure-semantic-similarity-of-gene-ontology-terms-by-their-definitions
#4
Dat Duong, Wasi Uddin Ahmad, Eleazar Eskin, Kai-Wei Chang, Jingyi Jessica Li
The gene ontology (GO) database contains GO terms that describe biological functions of genes. Previous methods for comparing GO terms have relied on the fact that GO terms are organized into a tree structure. Under this paradigm, the locations of two GO terms in the tree dictate their similarity score. In this article, we introduce two new solutions for this problem by focusing instead on the definitions of the GO terms. We apply neural network-based techniques from the natural language processing (NLP) domain...
October 31, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30328709/satrans-new-free-available-software-for-annotation-of-transcriptome-and-functional-analysis-of-differentially-expressed-genes
#5
Filip Zavadil Kokáš, Véronique Bergougnoux, Mária Majeská Čudejková
Recent technological advances have made next-generation sequencing (NGS) a popular and financially accessible technique allowing a broad range of analyses to be done simultaneously. A huge amount of newly generated NGS data, however, require advanced software support to help both in analyzing the data and biologically interpreting the results. In this article, we describe SATrans (Software for Annotation of Transcriptome), a software package providing fast and robust functional annotation of novel sequences obtained from transcriptome sequencing...
October 16, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30328692/ionhammer-homopolymer-space-hamming-clustering-for-iontorrent-read-error-correction
#6
Vasily Ershov, Artem Tarasov, Alla Lapidus, Anton Korobeynikov
We describe fast and accurate algorithm for IonTorrent read error correction capable of significantly reducing the number of sequencing errors over the wide range of data sets. IonHammer is implemented in C++ and is freely available as part of the SPAdes genome assembler package.
October 16, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30272994/improving-imputation-accuracy-by-inferring-causal-variants-in-genetic-studies
#7
Yue Wu, Farhad Hormozdiari, Jong Wha J Joo, Eleazar Eskin
Genotype imputation has been widely utilized for two reasons in the analysis of genome-wide association studies (GWAS). One reason is to increase the power for association studies when causal single nucleotide polymorphisms are not collected in the GWAS. The second reason is to aid the interpretation of a GWAS result by predicting the association statistics at untyped variants. In this article, we show that prediction of association statistics at untyped variants that have an influence on the trait produces is overly conservative...
October 1, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30251882/simultaneous-model-selection-and-model-calibration-for-the-proliferation-of-tumor-and-normal-cells-during-in-vitro-chemotherapy-experiments
#8
JosÉ M J Costa, Helcio R B Orlande, Viviane O F Lione, Antonio G F Lima, TaynÁ C S Cardoso, Leonardo A B Varón
In vitro experiments were conducted in this work to analyze the proliferation of tumor (DU-145) and normal (macrophage RAW 264.7) cells under the influence of a chemotherapeutic drug (doxorubicin). Approximate Bayesian Computation (ABC) was used to select among four competing models to represent the number of cells and to estimate the model parameters, based on the experimental data. For one case, the selected model was validated in a replicated experiment, through the solution of a state estimation problem with a particle filter algorithm, thus demonstrating the robustness of the ABC procedure used in this work...
September 22, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30234379/identify-cross-talk-between-circadian-rhythm-and-coronary-heart-disease-by-multiple-correlation-analysis
#9
Xiaoping Yan, Y U Huang, Jiabin Wu
Disorder in circadian rhythm has been revealed as a risk factor for coronary heart disease. Several studies in molecular biology established a gene interaction network using coronary heart susceptibility genes and the circadian rhythm pathway. However, cross talk between genes was mostly discovered in single gene pairs. There might be combination sets of genes intergraded as a unit to regulate the network. To resolve multiple variables in coronary heart susceptibility genes controlling circadian rhythm pathways, a multiple correlation analysis was applied to the transcriptome...
September 19, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30204477/the-insight-into-protein-ligand-interactions-a-novel-way-of-buffering-protein-noise-in-gene-expression
#10
Shih-Chiang Lo, Feng-You Liu, Wun-Sin Jhang, Che-Chi Shu
Random fluctuations are often considered detrimental in the context of gene regulation. Studies aimed at discovering the noise-buffering strategies are important. In this study, we demonstrated a novel design of attenuating noise at protein-level. The protein-ligand interaction dramatically reduced noise so that the coefficient of variation (COV) became roughly 1/3. Remarkably, in comparison to the other two noise-buffering methods, the negative feedback control and the incoherent feedforward loop, the COV of the target protein in the case of protein-ligand interaction appeared to be less than 1/2 of that of the other two methods...
September 11, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30204481/large-deviation-properties-of-sequence-alignment-of-correlated-sequences
#11
Matthias Werner, Pascal Fieth, Alexander Hartmann
The significance of alignment scores of optimally aligned DNA sequences can be estimated through the score distribution of pairs of random sequences. It is necessary to obtain statistics for the relevant high-scoring tail of the distribution. For local alignments of iid drawn sequences it has already been shown that the often assumed Gumbel distribution does not hold in the distribution tail, but has to be corrected by a Gaussian factor. Real DNA sequences were observed to show long-range correlations within sequences, which are not correctly modeled by iid random sequences...
September 10, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30204489/sequence-alignment-on-directed-graphs
#12
Vaddadi Naga Sai Kavya, Kshitij Tayal, Rajgopal Srinivasan, Naveen Sivadasan
Genomic variations in a reference collection are naturally represented as genome variation graphs. Such graphs encode common subsequences as vertices and the variations are captured using additional vertices and directed edges. The resulting graphs are directed graphs possibly with cycles. Existing algorithms for aligning sequences on such graphs make use of partial order alignment (POA) techniques that work on directed acyclic graphs (DAGs). To achieve this, acyclic extensions of the input graphs are first constructed through expensive loop unrolling steps (DAGification)...
September 8, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30204488/mitochondrial-morphologies-driven-by-energy-consuming-cell-sites-in-a-spatially-and-time-resolved-quality-model
#13
Daniel Mellem, Frank Fischer, Sören Jaspers, Horst Wenck, Michael Rübhausen
Mitochondria are the energy plants of eukaryotic cells. Mitochondrial network morphologies are essential for the energy supply of eukaryotic cells. However, the associated dynamics are not yet fully understood. They behave as a dynamic network that adapts to the cell's environment and its energetic needs. Various processes such as mitochondrial fission and fusion, mitochondrial recycling, repair mechanisms, and oxidative stress influence the state of the mitochondrial network. Here, we introduce a novel time-dependent and spatially resolved quality model on mitochondrial morphology...
September 8, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30204482/easyqc-tool-with-interactive-user-interface-for-efficient-next-generation-sequencing-data-quality-control
#14
Vijaya Raghavan Rangamaran, Bharathram Uppili, Dharani Gopal, Kirubagaran Ramalingam
The advent of next-generation sequencing (NGS) technologies has revolutionized the world of genomic research. Millions of sequences are generated in a short period of time and they provide intriguing insights to the researcher. Many NGS platforms have evolved over a period of time and their efficiency has been ever increasing. Still, primarily because of the chemistry, glitch in the sequencing machine and human handling errors, some artifacts tend to exist in the final sequence data set. These sequence errors have a profound impact on the downstream analyses and may provide misleading information...
September 8, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30204480/machine-learning-based-method-for-obesity-risk-evaluation-using-single-nucleotide-polymorphisms-derived-from-next-generation-sequencing
#15
Hsin-Yao Wang, Shih-Cheng Chang, Wan-Ying Lin, Chun-Hsien Chen, Szu-Hsien Chiang, Kai-Yao Huang, Bo-Yu Chu, Jang-Jih Lu, Tzong-Yi Lee
Obesity is a major risk factor for many metabolic diseases. To understand the genetic characteristics of obese individuals, single-nucleotide polymorphisms (SNPs) derived from next-generation sequencing (NGS) provide comprehensive insight into genome-wide genetic investigation. However, interpretation of these SNP data for clinical application is difficult given the high complexity of NGS data. Hence, in this study, obesity risk prediction models based on SNPs were designed using machine learning (ML) methods, namely support vector machine (SVM), k-nearest neighbor, and decision tree (DT)...
September 8, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30133328/an-efficient-dual-sampling-algorithm-with-hamming-distance-filtration
#16
Christopher Barrett, Qijun He, Fenix W Huang, Christian M Reidys
Recently, a framework considering ribonucleic acid (RNA) sequences and their RNA secondary structures as pairs has led to new information theoretic perspectives on how the semantics encoded in RNA sequences can be inferred. In this context, the pairing arises naturally from the energy model of RNA secondary structures. Fixing the sequence in the pairing produces the RNA energy landscape, whose partition function was discovered by McCaskill. Dually, fixing the structure induces the energy landscape of sequences...
November 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30133318/combinatorial-scoring-of-phylogenetic-trees-and-networks-based-on-homoplasy-free-characters
#17
Nikita Alexeev, Max A Alekseyev
Construction of phylogenetic trees and networks for extant species from their characters represents one of the key problems in phylogenomics. While solution to this problem is not always uniquely defined and there exist multiple methods for tree/network construction, it becomes important to measure how well the constructed networks capture the given character relationship across the species. We propose a novel method for measuring the specificity of a given phylogenetic network in terms of the total number of distributions of homoplasy-free character states at the leaves that the network may impose...
November 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30133315/sequential-integration-of-fuzzy-clustering-and-expectation-maximization-for-transcription-factor-binding-site-identification
#18
Ali Yousefian-Jazi, Jinwook Choi
The identification of transcription factor binding sites (TFBSs) is a problem for which computational methods offer great hope. Thus far, the expectation maximization (EM) technique has been successfully utilized in finding TFBSs in DNA sequences, but inappropriate initialization of EM has yielded poor performance or running time scalability under a given data set. In this study, we used a sequential integration approach that defined the final solution as the set of solutions acquired from solving objectives in a cascade manner to integrate the fuzzy C-means and the EM approaches to DNA motif discovery...
November 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30133311/probabilistic-modeling-of-pseudorabies-virus-infection-in-a-neural-circuit
#19
Siamak K Sorooshyari, Matthew P Taylor, H Vincent Poor
Viral transneuronal tracing methods effectively label synaptically connected neurons in a time-dependent manner. However, the modeling of viral vectors has been largely absent. An objective of this article is to motivate and initiate a basis for computational modeling of viral labeling and the questions that can be investigated through modeling of pseudorabies virus (PRV) virion progression in a neural circuit. In particular, a mathematical model is developed for quantitative analysis of PRV infection. Probability expressions are presented to evaluate the progression of viral labeling along the neural circuit...
November 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30133310/differential-expression-analysis-in-rna-seq-data-using-a-geometric-approach
#20
Tiago Tambonis, Marcelo Boareto, Vitor B P Leite
Although differential gene expression (DGE) profiling in RNA-seq is used by many researchers, new packages and pipelines are continuously being presented as a result of an ongoing investigation. In this work, a geometric approach based on Supervised Variational Relevance Learning (Suvrel) was compared with DEpackages (edgeR, DESEq, baySeq, PoissonSeq, and limma) in the DGE profiling. The Suvrel method seeks to determine the relevance of characteristics (e.g., gene or transcript) based on intraclass and interclass distances...
November 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
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