Advanced Data Mining Technologies in Bioinformatics

The technologies in data mining have been successfully applied to bioinformatics research in the past few years, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining plays an essential role in understanding the emerging problems in genomics, proteomics, and systems biology. Advanced Data Mining Technologies in Bioinformatics covers important research topics of data mining on bioinformatics. Readers of this book will gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. Advanced Data Mining Technologies in Bioinformatics is extremely useful for data mining researchers, molecular biologists, graduate students, and others interested in this topic. This Book Covers Research Topics Of Data Mining On Bioinformatics Presenting The Basics And Problems Of Bioinformatics And Applications Of Data Mining Technologies Pertaining To The Field--provided By Publisher. Introduction To Data Mining In Bioinformatics / Hui-huang Hsu, Tamkang -- Hierarchical Profiling, Scoring And Applications In Bioinformatics / Li Liao -- Combinatorial Fusion Analysis: Methods And Practices Of Combining Multiple Scoring Systems / D. Frank Hs, Yun-sheng Chung, Bruce S. Kristal -- Dna Sequence Visualization / Hsuan T. Chang -- Proteomics With Mass Spectrometry / Simon Lin, Salvatore Mungal, Richard Haney, Edward F. Patz, Jr., Patrick Mcconnell -- Efficient And Robust Analysis Of Large Phylogenetic Datasets / Sven Rahmann, Tobias Müller, Thomas Dandekar, Matthias Wolf -- Algorithmic Aspects Of Protein Threading / Tatsuya Akutsu -- Pattern Differentiations And Formulations For Heterogeneous Genomic Data Through Hybrid Approaches / Arpad Kelemen, Yulan Liang -- Parameterless Clustering Techniques For Gene Expression Analysis / Vincent S.m. Tseng, Ching-pin Kao -- Jointly Discriminatory Gene Selection For Molecular Classification Of Cancer / Junying Zhang -- A Haplotype Analysis System For Genes Discovery Of Common Diseases / Takashi Kido -- A Bayesian Framework For Improving Clustering Accuracy Of Protein Sequences Based On Association Rules / Peng-yeng Yin, Shyong-jian Shyu, Guan-shieng Huang, Shuang-te Liao -- In Silico Recognition Of Protein-protein Interactions: Theory And Applications / Byung-hoon Park, Phuongan Dam, Chongle Pan, Ying Xu, Al Geist, Grant Heffelfinger, Nagiza F. Samatova -- Differential Association Rules: Understanding Annotations In Protein Interaction Networks / Christopher Besemann, Anne Denton, Ajay Yekkirala, Ron Hutchison, Marc Anderson -- Mining Bioliterature: Toward Automatic Annotation Of Genes And Proteins / Francisco M. Couto, Mário J. Silva -- Comparative Genome Annotation Systems / Kwangmin Choi, Sun Kim. Hui-huang Hsu [editor]. Includes Bibliographical References And Index. The technologies in data mining have been applied to bioinformatics research in the past few years with success, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining plays a essential role in understanding the emerging problems in genomics, proteomics, and systems biology. Advanced Data Mining Technologies in Bioinformatics covers important research topics of data mining on bioinformatics. Readers of this book will gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. Advanced Data Mining Technologies in Bioinformatics is extremely useful for data mining researchers, molecular biologists, graduate students, and others interested in this topic. Covers several research topics of data mining on bioinformatics. This title helps readers gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. It is for researchers, molecular biologists, and others. Progress of information technologies has made the storage and distribution of data much easier in the past two decades.