The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge 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, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management.
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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.
Wiley Series on Bioinformatics: Computational Techniques and Engineering
Discover how data mining is fueling new discoveries in bioinformatics
As 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 searching
For 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.
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