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Informationen zum Autor Xiaohua Hu , PhD, is Assistant Professor of Computer Science in the College of Information Science and Technology at Drexel University. His research has been published in such journals as IEEE Computer, Knowledge and Information Systems, Journal of Intelligent Systems, and the International Journal of Applied Intelligence. Yi Pan , PhD, is Chair and Professor of Computer Science at Georgia State University. His pioneering work in computing using reconfigurable optical buses has been cited by researchers around the world. Dr. Pan is co-holder of three United States patents (pending) and five provisional patents. Klappentext Wiley Series on Bioinformatics: Computational Techniques and EngineeringDiscover how data mining is fueling new discoveries in bioinformaticsAs the field of bioinformatics continues to flourish, producing enormous amounts of new data, the need for sophisticated methods of data mining to better manage and extract meaning from bioinformatics data has grown tremendously. This pioneering text brings together an unparalleled group of leading experts in both data mining and bioinformatics. These experts present a broad range of novel methods, techniques, and applications of data mining for the analysis and management of bioinformatics data sets. Among the topics covered are:*RNA and protein structure analysis*DNA computing*Sequence mapping and genome comparison*Gene expression data mining*Metabolic network modeling*Phyloinformatics*Biomedical literature data mining*Biological data integration and searchingFor each topic, readers get an inside perspective into the latest research-what works and what doesn't and where additional research and development is needed. References to the primary literature facilitate further in-depth research.Data mining in bioinformatics holds the promise of solving such fundamental problems as protein structure, gene finding, data retrieval, and integration. This text is therefore essential reading for all researchers in bioinformatics, pointing them to new methods and techniques that may be the key to new and important discoveries. Zusammenfassung Aims to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing research topics such as gene expressions; protein/RNA structure prediction; phylogenetics; sequence and structural motifs; genomics and proteomics; gene findings; drug design; RNAi and microRNA analysis; and more. Inhaltsverzeichnis Contributors. Preface. 1 Current Methods for Protein Secondary-Structure Prediction Based on Support Vector Machines (Hae-Jin Hu, Robert W. Harrison, Phang C. Tai, and Yi Pan). 1.2 Support Vector Machine Method. 1.3 Performance Comparison of SVM Methods. 1.4 Discussion and Conclusions. 2 Comparison of Seven Methods for Mining Hidden Links (Xiaohua Hu, Xiaodan Zhang, and Xiaohua Zhou). 2.1 Analysis of the Literature on Raynaud's Disease. 2.2 Related Work. 2.3 Methods. 2.4 Experiment Results and Analysis. 2.5 Discussion and Conclusions. 3 Voting Scheme-Based Evolutionary Kernel Machines for Drug Activity Comparisons (Bo Jin and Yan-Qing Zhang). 3.1 Granular Kernel and Kernel Tree Design. 3.2 GKTSESs. 3.3 Evolutionary Voting Kernel Machines. 3.4 Simulations. 3.5 Conclusions and Future Work. 4 Bioinformatics Analyses of Arabidopsis thaliana Tiling Array Expression Data (Trupti Joshi, Jinrong Wan, Curtis J. Palm, Kara Juneau, Ron Davis, Audrey Southwick, Katrina M. Ramonell, Gary Stacey, and Dong Xu). 4.1 Tiling Array Design and Data Description. 4.2 Ontology Analyses. 4.3 Antisense Regulation Identification. 4.4 Correlated Expression Between Two DNA Strands. 4.5 Identification of Nonprotein Coding mRNA. 4.6 Summary. 5 Identi...
