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Download Special Issue BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Copyright © 2014 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data,JuliaTzu-YaWeng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Volume2014,ArticleID814092,3pages Evolution of Network Biomarkers from Early to Late Stage Bladder Cancer Samples,Yung-HaoWong, Cheng-Wei Li, and Bor-Sen Chen Volume 2014, Article ID 159078, 23 pages MicroRNA Expression Profiling Altered by Variant Dosage of Radiation Exposure,Kuei-FangLee, Yi-Cheng Chen, Paul Wei-Che Hsu, Ingrid Y. Liu, and Lawrence Shih-Hsin Wu Volume2014,ArticleID456323,10pages EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction, Chih-Hao Lu, Chin-Sheng Yu, Yu-Tung Chien, and Shao-Wei Huang Volume 2014, Article ID 807839, 12 pages High-Throughput Functional Screening of Steroid Substrates with Wild-Type and Chimeric P450 Enzymes, Philippe Urban, Gilles Truan, and Denis Pompon Volume 2014, Article ID 764102, 11 pages Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches, Chih-Min Chiu, Wei-Chih Huang, Shun-Long Weng, Han-Chi Tseng, Chao Liang, Wei-Chi Wang, Ting Yang, Tzu-Ling Yang, Chen-Tsung Weng, Tzu-Hao Chang, and Hsien-Da Huang Volume2014,ArticleID906168,10pages Studying the Complex Expression Dependences between Sets of Coexpressed Genes,MarioHuerta, Oriol Casanova, Roberto Barchino, Jose Flores, Enrique Querol, and Juan Cedano Volume 2014, Article ID 940821, 9 pages An Efficient Parallel Algorithm for Multiple Sequence Similarities Calculation Using a Low Complexity Method, Evandro A. Marucci, Geraldo F. D. Zafalon, Julio C. Momente, Leandro A. Neves, Carlo R. Valencio,ˆ Alex R. Pinto, Adriano M. Cansian, Rogeria C. G. de Souza, Yang Shiyou, and JoseM.Machado´ Volume2014,ArticleID563016,6pages The Definition of a Prolonged Intensive Care Unit Stay for Spontaneous Intracerebral Hemorrhage Patients: An Application with National Health Insurance Research Database, Chien-Lung Chan, Hsien-Wei Ting, and Hsin-Tsung Huang Volume 2014, Article ID 891725, 9 pages Gonadal Transcriptome Analysis of Male and Female Olive Flounder (Paralichthys olivaceus), Zhaofei Fan, Feng You, Lijuan Wang, Shenda Weng, Zhihao Wu, Jinwei Hu, Yuxia Zou, Xungang Tan, and Peijun Zhang Volume2014,ArticleID291067,10pages MAVTgsa: An R Package for Gene Set (Enrichment) Analysis, Chih-Yi Chien, Ching-Wei Chang, Chen-An Tsai, and James J. Chen Volume2014,ArticleID346074,11pages Target Capture and Massive Sequencing of Genes Transcribed in Mytilus galloprovincialis, Umberto Rosani, Stefania Domeneghetti, Alberto Pallavicini, and Paola Venier Volume 2014, Article ID 538549, 9 pages Defining Loci in Restriction-Based Reduced Representation Genomic Data from Nonmodel Species: Sources of Bias and Diagnostics for Optimal Clustering, Daniel C. Ilut, Marie L. Nydam, and Matthew P. Hare Volume2014,ArticleID675158,9pages MPINet: Metabolite Pathway Identification via Coupling of Global Metabolite Network Structure and Metabolomic Profile, Feng Li, Yanjun Xu, Desi Shang, Haixiu Yang, Wei Liu, Junwei Han, Zeguo Sun, Qianlan Yao, Chunlong Zhang, Jiquan Ma, Fei Su, Li Feng, Xinrui Shi, Yunpeng Zhang, Jing Li, Qi Gu, XiaLi,andChunquanLi Volume 2014, Article ID 325697, 14 pages miRSeq: A User-Friendly Standalone Toolkit for Sequencing Quality Evaluation and miRNA Profiling, Cheng-Tsung Pan, Kuo-Wang Tsai, Tzu-Min Hung, Wei-Chen Lin, Chao-Yu Pan, Hong-Ren Yu, and Sung-Chou Li Volume 2014, Article ID 462135, 8 pages Ultrasonographic Fetal Growth Charts: An Informatic Approach by Quantitative Analysis of the Impact of Ethnicity on Diagnoses Based on a Preliminary Report on Salentinian Population, Andrea Tinelli, Mario Alessandro Bochicchio, Lucia Vaira, and Antonio Malvasi Volume 2014, Article ID 386124, 10 pages Large-Scale Investigation of Human TF-miRNA Relations Based on Coexpression Profiles, Chia-Hung Chien, Yi-Fan Chiang-Hsieh, Ann-Ping Tsou, Shun-Long Weng, Wen-Chi Chang, and Hsien-Da Huang Volume 2014, Article ID 623078, 8 pages A De Novo Genome Assembly Algorithm for Repeats and Nonrepeats, Shuaibin Lian, Qingyan Li, Zhiming Dai, Qian Xiang, and Xianhua Dai Volume 2014, Article ID 736473, 16 pages Bioinformatic Prediction of WSSV-Host Protein-Protein Interaction, Zheng Sun, Shihao Li, Fuhua Li, and Jianhai Xiang Volume 2014, Article ID 416543, 9 pages High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data: A Comparative Study, Omid Hamidi, Lily Tapak, Aarefeh Jafarzadeh Kohneloo, and Majid Sadeghifar Volume 2014, Article ID 393280, 7 pages Hindawi Publishing Corporation BioMed Research International Volume 2014, Article ID 814092, 3 pages http://dx.doi.org/10.1155/2014/814092 Editorial Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Julia Tzu-Ya Weng,1,2 Li-Ching Wu,3 Wen-Chi Chang,4 Tzu-Hao Chang,5 Tatsuya Akutsu,6 and Tzong-Yi Lee1,2 1 Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan 2Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan 320, Taiwan 3Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan 320, Taiwan 4Institute of Tropical Plant Sciences, National Cheng Kung University, Tainan 701, Taiwan 5Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei 110, Taiwan 6Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto 611-0011, Japan Correspondence should be addressed to Tzong-Yi Lee; [email protected] Received 2 October 2014; Accepted 2 October 2014; Published 28 December 2014 Copyright © 2014 Julia Tzu-Ya Weng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction massive sequencing approach to reduce whole genome sequencing cost and effort. However, inferences from With the advent of high-throughput technologies, molec- sequencing data rely heavily on careful experimental design, ular biology is experiencing a surge in both growth and as well as efficient detection and removal of artifacts. While scope. As the amount of experimental data increases, the analyzing restriction-based reduced representation genomic demand for the development of ways to analyze these results data, D. C. Ilut et al. demonstrated that, by setting an optimal also increases. For example, the next-generation sequencing clustering threshold, false homozygosity or heterozygosity (NGS) technology has generated various sequencing data. can be effectively minimized. Mass spectrometry- (MS-) based experiments are also widely With the advancement of genomic researches, the num- applied in proteomics studies. Rapidly advancing technolo- ber of sequences processed in comparative methods has gies have offered us the opportunities to examine the genome, grownimmensely.E.A.Maruccietal.developedaparallel transcriptome, and proteome in comprehensive ways. Yet, algorithm for multiple sequence similarities calculation using extracting meaningful information from this vast sea of data the k-mers counting method. Their tests showed that the and approaching biological problems from systems biology algorithm provides a very good scalability and a nearly perspective have become the Holy Grail in bioinformat- linear speedup. In “Adenovogenomeassemblyalgorithmfor ics. The main focus of this special issue is novelty: new repeats and nonrepeats,” Z. Dai et al. proposed a new genome ideas, original research findings, and practical applications assembly algorithm called the sliding window assembler that intend to answer biological questions through high- (SWA), which assembles repeats and nonrepeats by adopting throughput technologies. The papers in this special issue a new overlapping extension strategy to extend each seed and present methods and experiments that demonstrate novel implementing a compensational mechanism for low coverage platforms and systems and new bioinformatics tools and datasets. Results of their analysis on three datasets support the models, as well as new data-analytical methods for high- practicability and efficiency of SWAas a promising algorithm throughput biological data. for NGS data. In this special issue, U. Rosani et al. attempted to High-throughput technology holds great promises for the unravel the genome of Mytilus galloprovincialis,theMediter- efficient investigation of transcriptomes, but the enormous ranean mussel, through a target capture and high-throughput amount of gene expression data
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