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IEEE/ACM Transactions on Computational Biology and Bioinformatics

Yue Zhang, Chunfang Zheng, David Sankoff
We outline a principled approach to the analysis of duplicate gene similarity distributions, based on a model integrating sequence divergence and the process of fractionation of duplicate genes resulting from whole genome duplication (WGD). This model allows us predict duplicate gene similarity distributions for series of two or three WGD, for whole genome triplication followed by a WGD, and for triplication, followed by speciation, followed by WGD. We calculate the probabilities of all possible fates of a gene pair as its two members proliferate or are lost, predicting the number of surviving pairs from each event...
July 14, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Nafiseh Sedaghat, Mahmood Fathy, Mohammad Hossein Modarressi, Ali Shojaie
MicroRNAs (miRNAs) are short non-coding RNAs which target mRNAs by binding to them and regulating their expression. Involvement of miRNAs has been discovered in many diseases, so it is fruitful to investigate the miRNAs and their targets to develop new therapeutic ways by designing anti-miRNA oligonucleotides. There are various computational methods to predict the target genes, however, their precisions are not good enough. In this paper, we apply a two-step approach to refine the results of sequence-based prediction algorithms...
July 13, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Nha Nguyen, An Vo, Haibin Sun, Heng Huang
Most existing array comparative genomic hybridization (array CGH) data processing methods and evaluation models assumed that the probability density function of noise in array CGH is a Gaussian distribution. However, in practice such noise distribution is peaky and heavy-tailed. A more accurate and sufficient model of noise in array CGH data is necessary and beneficial to the detection of DNA copy number variations. We analyze the real array CGH data from different platforms and show that the distribution of noise in array CGH data is fitted very well by generalized Gaussian distribution (GGD)...
July 6, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Wenbin Xie, Hong Yan, Xing-Ming Zhao
The microRNAs (miRNAs), regulators of post-transcriptional processes, have been found to affect the efficacy of drugs by regulating the biological processes in which the target proteins of drugs may be involved. For example, some drugs develop resistance when certain miRNAs are overexpressed. Therefore, identifying miRNAs that affect drug effects can help understand the mechanisms of drug actions and design more efficient drugs. Although some computational approaches have been developed to predict miRNA-drug associations, such associations rarely provide explicit information about which miRNAs and how they affect drug efficacy...
July 6, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Shifu Chen, Ming Liu, Xiaoni Zhang, Renwen Long, Yixing Wang, Yue Han, Shiwei Zhang, Mingyan Xu, Jia Gu
Plasma cell-free DNA (cfDNA) has certain fragmentation patterns, which can bring non-random base content curves of the sequencing data's beginning cycles. We studied the patterns and found that we could determine whether a sample is cfDNA or not by just looking into the first 10 cycles of its base content curves. We analysed 3189 FastQ files, including 1442 cfDNA, 1234 genomic DNA, 507 FFPE tumour DNA and 6 urinary cfDNA. By deep analysing these data, we find the patterns are stable enough to distinguish cfDNA from other kinds of DNA samples...
July 4, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Chunjiang Yu, Wentao Wu, Jing Wang, Yuxin Lin, Yang Yang, Jiajia Chen, Fei Zhu, Bairong Shen
With the widespread implementation of next-generation sequencing (NGS) technologies, millions of sequences have been produced. A lot of databases were created to store and organize the high-throughput sequencing data. Numerous analysis software programs and tools have been developed over the past years. Most of them use specific formats for data representation and storage. Data interoperability becomes a crucial challenge and many tools have been developed to convert NGS data from one format to another. However, most of them were developed for specific and limited formats...
July 3, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Karlene Nicole Meyer, Michelle Lacey
Variation in cytosine methylation at CpG dinucleotides is often observed in genomic regions, and analysis typically focuses on estimating the proportion of methylated sites observed in a given region and comparing these levels across samples to determine association with conditions of interest. While sites are tacitly treated as independent, when observed at the level of individual molecules methylation patterns exhibit strong evidence of local spatial dependence. We previously developed a neighboring sites model to account for correlation and clustering behavior observed in two tandem repeat regions in a collection of ovarian carcinomas...
June 30, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Roman Sergeevich Sergeev, Ivan Kavaliou, Uladzislau Sataneuski, Andrei Gabrielian, Alex Rosenthal, Michael Tartakovsky, Alexander Tuzikov
Emergence of drug-resistant microorganisms has been recognized as a serious threat to public health worldwide. This problem is extensively discussed in the context of tuberculosis treatment. Alterations in pathogen genomes are among the main mechanisms by which microorganisms exhibit drug resistance. Analysis of 144 M. tuberculosis strains of different phenotypes including drug susceptible, MDR and XDR isolated in Belarus was fulfilled in this paper. A wide range of machine learning methods that can discover SNPs related to drug-resistance in the whole bacteria genomes was investigated...
June 27, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Manuel Lafond, Cedric Chauve, Nadia El-Mabrouk, Aida Ouangraoua
The supertree problem asking for a tree displaying a set of consistent input trees has been largely considered for the reconstruction of species trees. Here, we explore this framework for the sake of reconstructing a gene tree from a set of input gene trees on partial data. The phylogenetic tree for the species containing the genes of interest can be used to choose among the many possible compatible "supergenetrees", a natural criteria being the reconciliation cost. We develop a variety of algorithmic solutions for the construction of gene trees using the supertree framework...
June 27, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
FanChang Hao, Melvin Zhang, Hon Wai Leong
We consider the problem of sorting signed permutations by reversals, transpositions, transreversals, and block-interchanges and give a 2-approximation scheme, called the GSB (Genome Sorting by Bridges) scheme. Our result extends 2-approximation algorithm of He and Chen [12] that allowed only reversals and block-interchanges, and also the 1.5 approximation algorithm of Hartman and Sharan [11] that allowed only transreversals and transpositions. We prove this result by introducing three bridge structures in the breakpoint graph, namely, the L-bridge, T-bridge, and X-bridge and show that they model "proper" reversals, transpositions, transreversals, and block-interchanges, respectively...
June 27, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Alexey Markin, Oliver Eulenstein
Median tree problems are powerful tools for inferring large-scale phylogenetic trees that hold enormous promise for society at large. Such problems seek a median tree for a given collection of input trees under some problem-specific distance. Here, we introduce a median tree problem under the classic Manhattan path-difference distance. We show that this problem is NP-hard, devise an ILP formulation, and provide an effective local search heuristic that is based on solving a local search problem exactly. Our algorithm for the local search problem improves asymptotically by a factor of n on the best-known (naive) solution, where n is the overall number of taxa in the input trees...
June 22, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Liliana Ironi, Ettore Lanzarone
Computational and mathematical models have significantly contributed to the rapid progress in the study of gene regulatory networks (GRN), but researchers still lack a reliable model-based framework for computer-aided analysis and design. Such tool should both reveal the relation between network structure and dynamics and find parameter values and/or constraints that enable the simulated dynamics to reproduce specific behaviors. This paper addresses these issues and proposes a computational framework that facilitates network analysis or design...
June 19, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Shaoliang Peng, Shunyun Yang, Wenhe Su, Xiaoyu Zhang, Tenglilang Zhang, Weiguo Liu, Xingming Zhao
Molecular Dynamics (MD) is the simulation of the dynamic behavior of atoms and molecules. As the most popular software for molecular dynamics, GROMACS cannot work on large-scale data because of limit computing resources. In this paper, we propose a CPU and IntelĀ® Xeon Phi Many Integrated Core (MIC) collaborated parallel framework to accelerate GROMACS using the offload mode on a MIC coprocessor, with which the performance of GROMACS is improved significantly, especially with the utility of Tianhe-2 supercomputer...
June 16, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Guoxian Yu, Guangyuan Fu, Jun Wang, Yingwen Zhao
A remaining key challenge of modern biology is annotating the functional roles of proteins. Various computational models have been proposed for this challenge. Most of them assume the annotations of annotated proteins are complete. But in fact, many of them are incomplete. We proposed a method called NewGOA to predict new Gene Ontology (GO) annotations for incompletely annotated proteins and for completely un-annotated ones. NewGOA employs a hybrid graph, composed of two types of nodes (proteins and GO terms), to encode interactions between proteins, hierarchical relationships between terms and available annotations of proteins...
June 15, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Xinyu He, Lishuang Li, Yang Liu, XiaoMing Yu, Jun Meng
Extracting biomedical events from biomedical literature plays an important role in the field of biomedical text mining, and the trigger detection is a key step in biomedical event extraction. We propose a two-stage method for trigger detection, which divides trigger detection into recognition stage and classification stage, and different features are selected in each stage. In the first stage, we select the features which are more suitable for recognition, and in the second stage, the features that are more helpful to classification are adopted...
June 13, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Shuai An, Jun Wang, Jinmao Wei
Selecting functional genes is essential for analyzing microarray data. Among many available feature (gene) selection approaches, the ones on the basis of the large margin nearest neighbor receive more attention due to their low computational costs and high accuracies in analyzing the high-dimensional data. Yet there still exist some problems that hamper the existing approaches in sifting real target genes, including selecting erroneous nearest neighbors, high sensitivity to irrelevant genes, and inappropriate evaluation criteria...
June 7, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Chun-Qiu Xia, Ke Han, Yong Qi, Yang Zhang, Dong-Jun Yu
Accurate identification of the cancer types is essential to cancer diagnoses and treatments. Since cancer tissue and normal tissue have different gene expression, gene expression data can be used as an efficient feature source for cancer classification. However, accurate cancer classification directly using original gene expression profiles remains challenging due to the intrinsic high-dimension feature and the small size of the data samples. We proposed a new self-training subspace clustering algorithm under low-rank representation, called SSC-LRR, for cancer classification on gene expression data...
June 6, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Misagh Kordi, Mukul S Bansal
Duplication-Transfer-Loss (DTL) reconciliation is a powerful method for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation seeks to reconcile gene trees with species trees by postulating speciation, duplication, transfer, and loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. In practice, however, gene trees are often non-binary due to uncertainty in the gene tree topologies, and DTL reconciliation with non-binary gene trees is known to be NP-hard...
June 1, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Qian Xie, Xiaoyan He, Fangji Yang, Xuling Liu, Ying Li, Yujing Liu, ZhengMeng Yang, Jianhai Yu, Bao Zhang, Wei Zhao
The outbreak of Middle East respiratory syndrome-coronavirus (MERS-CoV) in South Korea in April 2015 led to 186 infections and 37 deaths by the end of October 2015. MERS-CoV was isolated from the imported patient in China. The envelope (E) protein, a small structural protein of MERS-CoV, plays an important role in host recognition and infection. To identify the conserved epitopes of the E protein, sequence analysis was performed by comparing the E proteins from 42 MERS-CoV strains that triggered severe pandemics and infected humans in the past...
May 29, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Olivia Choudhury, Ankush Chakrabarty, Scott J Emrich
High-throughput sequencing techniques have generated massive quantities of genotype data. Haplotype phasing has proven to be a useful and effective method for analyzing these data. However, the quality of phasing is undermined by the presence of missing information. Imputation provides an effective means of improving the underlying genotype information. For model organisms, imputation can rely on an available reference genotype panel and a physical or genetic map. For non-model organisms, which often do not have a genotype panel, it is important to design an imputation technique that does not rely on reference data...
May 26, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
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