Biological Data Mining in Protein Interaction Networks

Biological Data Mining in Protein Interaction Networks

Indexed In: SCOPUS View 1 More Indices
Release Date: May, 2009|Copyright: © 2009 |Pages: 450
DOI: 10.4018/978-1-60566-398-2
ISBN13: 9781605663982|ISBN10: 1605663980|EISBN13: 9781605663999
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Description & Coverage
Description:

Methods for detecting protein-protein interactions (PPIs) have given researchers a global picture of protein interactions on a genomic scale.

Biological Data Mining in Protein Interaction Networks explains bioinformatic methods for predicting PPIs, as well as data mining methods to mine or analyze various protein interaction networks. A defining body of research within the field, this book discovers underlying interaction mechanisms by studying intra-molecular features that form the common denominator of various PPIs.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Data mining for biologists
  • Discovering interaction motifs
  • Discovering lethal proteins
  • Discovering protein complexes
  • Molecular biology of protein-protein interactions
  • Network motifs in protein interaction networks
  • Predicting protein functions
  • Predicting protein-protein interactions
  • Prioritizing disease genes
  • Protein interaction networks
  • Reliable protein interaction networks
Reviews & Statements

This is a valuable resource for researchers, biologists, computer scientists, postgraduate students, and others interested in the field of biological data mining in protein-protein interaction networks that will help illuminate the inner working mechanisms of cells, thereby enabling understanding of underlying disease pathways an discovery of new drugs.

– Doody's Review Service

The objective of this book is to disseminate the research results and best practice from cross-disciplinary researchers and practitioners interested in, and working on bioinformatics, data mining, and proteomics.

– Xiao-Li Li, Institute for Infocomm Research, Singapore
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Editor/Author Biographies
Xiao-Li Li is currently a principal investigator in the Data Mining Department at the Institute for Infocomm Research, A*Star. He also holds an appointment of adjunct assistant professor in SCE, NTU. Xiao-Li received his PhD degree in computer science from Chinese Academy of Sciences (2001) and was then with National University of Singapore (School of Computing/Singapore-MIT Alliance) as a research fellow from 2001 to 2004. His research interests include bioinformatics, data mining, and machine learning. He has been serving as a member of technical program committees in numerous bioinformatics (a book editor for Biological Data Mining in Protein Interaction Networks, PC members for IEEE BIBE, IEEE BIBM, etc.), data mining (including a PC member in leading data mining conference KDD, CIKM, and SDM), and machine learning related conferences (a session chair of PKDD/ECML). He has also served as an editorial board member for International Journal of Data Analysis Techniques and Strategies (IJDATS), Journal of Information Technology Research (JITR) and other IGI Global editorial advisory review boards. In 2005, he received best paper award in the 16th International Conference on genome informatics (GIW 2005). In 2008, he received the best poster award in the 12th Annual International Conference Research in computational molecular biology (RECOMB 2008). To learn more about Dr. Xiao-Li Li, please visit his Web page: http://www1.i2r.a-star.edu.sg/~xlli/.
See-Kiong Ng is currently the Department Head of the Data Mining Department at the Institute for Infocomm Research. He is also an adjunct associate professor at the School of Computer Engineering, Nanyang Technological University. Dr. Ng obtained his PhD in computer science from Carnegie Mellon University. He wrote the TrueAllele software when he was a graduate student at CMU. The program was eventually used by a biotech company in Iceland to genotype the entire Icelandic population, thereby beginning his brave journey into the exciting field of genomics as a computer scientist. Dr. Ng's current research focuses on unraveling the underlying functional mechanisms of protein interaction networks as well as other real-world networks. His continuing and emerging diverse and cross-disciplinary research interests include bioinformatics, text mining, social network mining, and privacy-preserving data mining.
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Editorial Advisory Board
  • Vlad Bajic, South African National Bioinformatics Institute, South Africa
  • Daisuke Kihara, Purdue University, USA
  • Hiroshi Mamitsuka, Kyoto University, Japan
  • N. Srinivasan, Indian Institute of Science, India
  • Jerzy Tiuryn, Warsaw University, Poland
  • Anna Tramontano, University of Rome "La Sapienza," Italy
  • Aidong Zhang, State University of New York at Buffalo, USA