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IEEE/ACM Transactions on Computational Biology and Bioinformatics

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https://www.readbyqxmd.com/read/28212095/identifying-bacterial-essential-genes-based-on-a-feature-integrated-method
#1
Yan Lin, Fa-Zhan Zhang, Kai Xue, Yi-Zhou Gao, Feng-Biao Guo
Essential genes are those genes of an organism that are considered to be crucial for its survival. Identification of essential genes is therefore of great significance to advance our understanding of the principles of cellular life. We have developed a novel computational method, which can effectively predict bacterial essential genes by extracting and integrating homologous features, protein domain feature, gene intrinsic features and network topological features. By performing the principal component regression (PCR) analysis for Escherichia coli MG1655, we established a classification model with the average area under curve (AUC) value of 0...
February 15, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28212094/characteristics-of-myosin-v-processivity
#2
Jun-Ping Zhang, Yi Liu, Wei Sun, Xiaoyang Zhao, Ta La, Wei-Sheng Guo
Myosin V is a processive doubled-headed biomolecular motor involved in many intracellular organelle and vesicle transport. The unidirectional movement is coupled with the adenosine triphosphate (ATP) hydrolysis and product release cycle. With the progress of experimental techniques and the enhancement of measuring directness, detailed knowledge of the motility of myosin V has been obtained.Following the ATPase cycle, the 4-state mechanochemical model of the myosin V's processive movement is used. The transitions between various states take place in a stochastic manner...
February 14, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28212093/predicting-antimicrobial-peptides-by-using-increment-of-diversity-with-quadratic-discriminant-analysis-method
#3
Pengmian Feng, Zhenyi Wang, Xiaoyu Yu
Antimicrobial peptides are crucial components of the innate host defense system of most living organisms and promising candidates for antimicrobial agents. Accurate classification of antimicrobial peptides will be helpful to the discovery of new therapeutic targets. In this work, the Increment of Diversity with Quadratic Discriminant analysis (IDQD) was presented to classify antifungal and antibacterial peptides based on primary sequence information. In the jackknife test, the proposed IDQD model yields an accuracy of 86...
February 14, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28186907/identifying-sigma70-promoters-with-novel-pseudo-nucleotide-composition
#4
Hao Lin, Zhi-Yong Liang, Hua Tang, Wei Chen
Promoters are DNA regulatory elements located directly upstream or at the 5' end of the transcription initiation site (TSS), which are in charge of gene transcription initiation. With the completion of a large number of microorganism genomics, it is urgent to predict promoters accurately in bacteria by using computational method. In this work, a sequence-based predictor named "iPro70-PseZNC" was designed for identifying sigma70 promoters in prokaryote. In the predictor, the samples of DNA sequences are formulated by a novel pseudo nucleotide composition, called PseZNC, into which the multi-window Z-curve composition and six local DNA structural properties are incorporated...
February 8, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28186906/regularized-non-negative-matrix-factorization-for-identifying-differential-genes-and-clustering-samples-a-survey
#5
Jin-Xing Liu, Dong Wang, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu, Jiguo Yu
Non-negative Matrix Factorization (NMF), a classical method for dimensionality reduction, has been applied in many fields. It is based on the idea that negative numbers are physically meaningless in various data-processing tasks. Apart from its contribution to conventional data analysis, the recent overwhelming interest in NMF is due to its newly discovered ability to solve challenging data mining and machine learning problems, especially in relation to gene expression data. This survey paper mainly focuses on research examining the application of NMF to identify differentially expressed genes and to cluster samples, and the main NMF models, properties, principles, and algorithms with its various generalizations, extensions, and modifications are summarized...
February 7, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28186905/hmmcas-a-web-tool-for-the-identification-and-domain-annotations-of-cas-proteins
#6
Guoshi Chai, Min Yu, Lixu Jiang, Yaocong Duan, Jian Huang
The CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated proteins) adaptive immune systems are discovered in many bacteria and most archaea. These systems are encoded by cas (CRISPR-associated) operons that have an extremely diverse architecture. The most crucial step in the depiction of cas operons composition is the identification of cas genes or Cas proteins. With the continuous increase of the newly sequenced archaeal and bacterial genomes, the recognition of new Cas proteins is becoming possible, which not only provides candidates for novel genome editing tools but also helps to understand the prokaryotic immune system better...
February 7, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28186904/a-combined-pls-and-negative-binomial-regression-model-for-inferring-association-networks-from-next-generation-sequencing-count-data
#7
Maiju Pesonen, Jaakko Nevalainen, Steven Potter, Somnath Datta, Susmita Datta
A major challenge of genomics data is to detect interactions displaying functional associations from large-scale observations. In this study, a new cPLS-algorithm combining partial least squares approach with negative binomial regression is suggested to reconstruct a genomic association network for high-dimensional next-generation sequencing count data. The suggested approach is applicable to the raw counts data, without requiring any further pre-processing steps. In the settings investigated, the cPLS-algorithm outperformed the two widely used comparative methods, graphical lasso and weighted correlation network analysis...
February 7, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28186903/construction-of-refined-protein-interaction-network-for-predicting-essential-proteins
#8
Min Li, Peng Ni, Xiaopei Chen, Jianxin Wang, Fangxiang Wu, Yi Pan
Identification of essential proteins based on protein interaction network (PIN) is a very important and hot topic in the post genome era. Up to now, a number of network-based essential protein discovery methods have been proposed. Generally, a static protein interaction network was constructed by using the protein-protein interactions obtained from different experiments or databases. Unfortunately, most of the network-based essential protein discovery methods are sensitive to the reliability of the constructed PIN...
February 7, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28166504/the-scj-small-parsimony-problem-for-weighted-gene-adjacencies
#9
Nina Luhmann, Manuel Lafond, Annelyse Thevenin, Aida Ouangraoua, Roland Wittler, Cedric Chauve
Reconstructing ancestral gene orders in a given phylogeny is a classical problem in comparative genomics. Most existing methods compare conserved features in extant genomes in the phylogeny to define potential ancestral gene adjacencies, and either try to reconstruct all ancestral genomes under a global evolutionary parsimony criterion, or, focusing on a single ancestral genome, use a scaffolding approach to select a subset of ancestral gene adjacencies, generally aiming at reducing the fragmentation of the reconstructed ancestral genome...
January 31, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28113348/a-just-in-time-learning-based-monitoring-and-classification-method-for-hyper-hypocalcemia-diagnosis
#10
Xin Peng, Yang Tang, Wangli He, Wenli Du, Feng Qian
This study focuses on the classification and pathological status monitoring of hyper/hypo-calcemia in the calcium regulatory system. By utilizing the Independent Component Analysis (ICA) mixture model, samples from healthy patients are collected, diagnosed, and subsequently classified according to their underlying behaviors, characteristics, and mechanisms. Then, a Just-in-Time Learning (JITL) has been employed in order to estimate the diseased status dynamically. In terms of JITL, for the purpose of the construction of an appropriate similarity index to identify relevant datasets, a novel similarity index based on the ICA mixture model is proposed in this paper to improve online model quality...
January 20, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28092574/dynamics-in-epistasis-analysis
#11
Aseel Awdeh, Hilary Phenix, Mads Kaern, Theodore Perkins
Finding regulatory relationships between genes, including the direction and nature of influence between them, is a fundamental challenge in the field of molecular genetics. One classical approach to this problem is epistasis analysis. Broadly speaking, epistasis analysis infers the regulatory relationships between a pair of genes in a genetic pathway by considering the patterns of change in an observable trait resulting from single and double deletion of genes. While classical epistasis analysis has yielded deep insights on numerous genetic pathways, it is not without limitations...
January 16, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28092573/environment-sensitivity-based-cooperative-co-evolutionary-algorithms-for-dynamic-multi-objective-optimization
#12
Biao Xu, Yong Zhang, Dunwei Gong, Yinan Guo, Miao Rong
Dynamic multi-objective optimization problems (DMOPs) not only involve multiple conflicting objectives, but these objectives may also vary with time, raising a challenge for researchers to solve them. This paper presents a cooperative co-evolutionary strategy based on environment sensitivities for solving DMOPs. In this strategy, a new method that groups decision variables is first proposed, in which all the decision variables are partitioned into two subcomponents according to their interrelation with environment...
January 16, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28092572/pspel-in-silico-prediction-of-self-interacting-proteins-from-amino-acids-sequences-using-ensemble-learning
#13
Jian-Qiang Li, Zhu-Hong You, Xiao Li, Ming Zhong, Xing Chen
Self interacting proteins (SIPs) play an important role in various aspects of the structural and functional organization of the cell. Detecting SIPs is one of the most important issues in current molecular biology. Although a large number of SIPs data has been generated by experimental methods, wet laboratory approaches are both time-consuming and costly. In addition, they yield high false negative and positive rates. Thus, there is a great need for in silico methods to predict SIPs accurately and efficiently...
January 10, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28026781/exploring-consensus-rna-substructural-patterns-using-subgraph-mining
#14
Qingfeng Chen, Chaowang Lan, Baoshan Chen, Lusheng Wang, Jinyan Li, Chengqi Zhang
Frequently recurring RNA structural motifs play important roles in RNA folding process and interaction with other molecules. Traditional index-based and shape-based schemas are useful in modeling RNA secondary structures but ignore the structural discrepancy of individual RNA family member. Further, the in-depth analysis of underlying substructure pattern is insufficient due to varied and unnormalized substructure data. This prevents us from understanding RNAs functions and their inherent synergistic regulation networks...
December 26, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28029629/discovering-perturbation-of-modular-structure-in-hiv-progression-by-integrating-multiple-data-sources-through-non-negative-matrix-factorization
#15
Sumanta Ray, Ujjwal Maulik
Detecting perturbation in modular structure during HIV-1 disease progression is an important step to understand stage specific infection pattern of HIV-1 virus in human cell. In this article, we proposed a novel methodology on integration of multiple biological information to identify such disruption in human gene module during different stages of HIV-1 infection. We integrate three different biological information: gene expression information, protein-protein interaction information and gene ontology information in single gene meta-module, through non negative matrix factorization (NMF)...
December 20, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28029628/evolutionary-graph-clustering-for-protein-complex-identification
#16
Tiantian He, Keith C C Chan
This paper presents a graph clustering algorithm, called EGCPI, to discover protein complexes in protein-protein interaction (PPI) networks. In performing its task, EGCPI takes into consideration both network topologies and attributes of interacting proteins, both of which have been shown to be important for protein complex discovery. EGCPI formulates the problem as an optimization problem and tackles it with evolutionary clustering. Given a PPI network, EGCPI first annotates each protein with corresponding attributes that are provided in Gene Ontology database...
December 20, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28113329/the-discovery-of-mutated-driver-pathways-in-cancer-models-and-algorithms
#17
Junhua Zhang, Shihua Zhang
The pathogenesis of cancer in human is still poorly understood. With the rapid development of high-throughput sequencing technologies, huge volumes of cancer genomics data have been generated. Deciphering those data poses great opportunities and challenges to computational biologists. One of such key challenges is to distinguish driver mutations, genes as well as pathways from passenger ones. Mutual exclusivity of gene mutations (each patient has no more than one mutation in the gene set) has been observed in various cancer types and thus has been used as an important property of a driver gene set or pathway...
December 15, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28113328/network-regularized-sparse-logistic-regression-models-for-clinical-risk-prediction-and-biomarker-discovery
#18
Wenwen Min, Juan Liu, Shihua Zhang
Molecular profiling data (e.g., gene expression) has been used for clinical risk prediction and biomarker discovery. However, it is necessary to integrate other prior knowledge like biological pathways or gene interaction networks to improve the predictive ability and biological interpretability of biomarkers. Here, we first introduce a general regularized Logistic Regression (LR) framework with regularized term kwk1 + wTMw, which can reduce to different penalties, including Lasso, elastic net, and network-regularized terms with differentM...
December 15, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28113327/efficient-quartet-representations-of-trees-and-applications-to-supertree-and-summary-methods
#19
Ruth Davidson, MaLyn Lawhorn, Joseph Rusinko, Noah Weber
Quartet trees displayed by larger phylogenetic trees have long been used as inputs for species tree and supertree reconstruction. Computational constraints prevent the use of all displayed quartets in many practical problems with large numbers of taxa. We introduce the notion of an Efficient Quartet System (EQS) to represent a phylogenetic tree with a subset of the quartets displayed by the tree. We show mathematically that the set of quartets obtained from a tree via an EQS contains all of the combinatorial information of the tree itself...
December 14, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/27992348/efficient-quartet-representations-of-trees-and-applications-to-supertree-and-summary-methods
#20
Ruth Davidson, MaLyn Lawhorn, Joseph Rusinko, Noah Weber
Quartet trees displayed by larger phylogenetic trees have long been used as inputs for species tree and supertree reconstruction. Computational constraints prevent the use of all displayed quartets in many practical problems with large numbers of taxa. We introduce the notion of an Efficient Quartet System (EQS) to represent a phylogenetic tree with a subset of the quartets displayed by the tree. We show mathematically that the set of quartets obtained from a tree via an EQS contains all of the combinatorial information of the tree itself...
December 14, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
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