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

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https://www.readbyqxmd.com/read/30234379/identify-cross-talk-between-circadian-rhythm-and-coronary-heart-disease-by-multiple-correlation-analysis
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
#7
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
#8
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...
August 22, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30133320/bootstrapping-time-course-gene-expression-data-for-gene-networks-application-to-gene-relevance-networks
#9
Jeonifer M Garren, Jaejik Kim
Identification of gene regulatory networks (GRNs) is a fundamental step to understand the molecular role of each gene and it helps to develop treatment and cure of a disease. To identify GRNs, time-course gene expression data are widely used. However, the identification is hampered by intrinsic attributes of the data such as small sample size, a large number of variables, and complex error structures with high variation. Under this situation, most GRN inference methods utilize point estimators or make numerous assumptions that are often incompatible with the experimental data...
August 22, 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
#10
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...
August 22, 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
#11
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...
August 22, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30133312/structure-aware-principal-component-analysis-for-single-cell-rna-seq-data
#12
Snehalika Lall, Debajyoti Sinha, Sanghamitra Bandyopadhyay, Debarka Sengupta
With the emergence of droplet-based technologies, it has now become possible to profile transcriptomes of several thousands of cells in a day. Although such a large single-cell cohort may favor the discovery of cellular heterogeneity, it also brings new challenges in the prediction of minority cell types. Identification of any minority cell type holds a special significance in knowledge discovery. In the analysis of single-cell expression data, the use of principal component analysis (PCA) is surprisingly frequent for dimension reduction...
August 22, 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
#13
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...
August 22, 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
#14
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...
August 22, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30117753/a-simple-approach-to-the-reconstruction-of-a-set-of-points-from-the-multiset-of-pairwise-distances-in-n-2-steps-for-the-sequencing-problem-iii-noise-inputs-for-the-beltway-case
#15
Eduard Fomin
The approach based on the removal of redundancy in inputs when reconstructing a set of points X from the set of their pairwise distances [Formula: see text] is generalized for the beltway case by using integral transformations. It is shown that the generalized approach can be successfully used not only for complete and error-free sets of pairwise distances [Formula: see text], but also for sets [Formula: see text] containing a large number of noise and missing data [Formula: see text]. The proposed approach allows to reconstruct X in n2 steps, where n is the cardinality of noise input sets...
August 17, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30117747/joker-de-bruijn-covering-k-mers-using-joker-characters
#16
Yaron Orenstein, Yun William Yu, Bonnie Berger
Sequence libraries that cover all k-mers enable universal and unbiased measurements of nucleotide and peptide binding. The shortest sequence to cover all k-mers is a de Bruijn sequence of length [Formula: see text]. Researchers would like to increase k to measure interactions at greater detail, but face a challenging problem: the number of k-mers grows exponentially in k, while the space on the experimental device is limited. In this study, we introduce a novel advance to shrink k-mer library sizes by using joker characters, which represent all characters in the alphabet...
August 17, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30117746/two-exponential-models-of-gene-expression-patterns-for-noisy-experimental-data
#17
Theodore Alexandrov, Nina Golyandina, David Holloway, Alex Shlemov, Alexander Spirov
Spatial pattern formation of the primary anterior-posterior morphogenetic gradient of the transcription factor Bicoid (Bcd) has been studied experimentally and computationally for many years. Bcd specifies positional information for the downstream segmentation genes, affecting the fly body plan. More recently, a number of researchers have focused on the patterning dynamics of the underlying bcd messenger RNA (mRNA) gradient, which is translated into Bcd protein. New, more accurate techniques for visualizing bcd mRNA need to be combined with quantitative signal extraction techniques to reconstruct the bcd mRNA distribution...
August 17, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30117742/a-workflow-to-improve-variant-calling-accuracy-in-molecular-barcoded-sequencing-reads
#18
Michael Ta, Changchuan Yin, Gary Lee Smith, Wenbo Xu
Multiplexed molecular barcoded amplicon sequencing has been previously demonstrated to improve the sensitivity of low-frequency variant detection. Molecular barcoded reads can be used to identify and correct amplification biases introduced during library preparation and sequencing errors. We propose a generic workflow to improve variant calling accuracy that takes advantage of molecular barcoded sequencing reads by applying a base score correction method to duplicate or overlapping read pairs across the targeted panel...
August 17, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30113871/irna-2om-a-sequence-based-predictor-for-identifying-2-o-methylation-sites-in-homo-sapiens
#19
Hui Yang, Hao Lv, Hui Ding, Wei Chen, Hao Lin
2'-O-methylation plays an important biological role in gene expression. Owing to the explosive increase in genomic sequencing data, it is necessary to develop a method for quickly and efficiently identifying whether a sequence contains the 2'-O-methylation site. As an additional method to the experimental technique, a computational method may help to identify 2'-O-methylation sites. In this study, based on the experimental 2'-O-methylation data of Homo sapiens, we proposed a support vector machine-based model to predict 2'-O-methylation sites in H...
August 16, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/30113868/edop-distance-between-sets-of-incomplete-permutations-application-to-bacteria-classification-based-on-gene-order
#20
Xinrui Zhou, Amihood Amir, Concettina Guerra, Gadi Landau, Jarek Rossignac
In this work, we extend measures of distance between permutations to support incomplete permutations. Modeling and comparing incomplete permutations are a challenging computational problem of practical importance in many applications in bioinformatics and social science. We show that the proposed distance measure admits a closed-form expression and can be efficiently computed on sets of permutations involving several missing elements. We demonstrate the proposed method on the classification of bacteria from different phyla based on gene order...
August 16, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
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