Biological Data Mining in Protein Interaction Networks

Erscheinungsjahr 2009
ISBN: 978-1-60566-398-2
Verlag: Medical Information Science Reference

Buch, Englisch, 437 Seiten, Hardback, Format (B × H): 221 mm x 286 mm, Gewicht: 1384 g

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.

Autoren/Hrsg.

Li, Xiao-Li

Ng, See-Kiong

Inhaltsverzeichnis

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

Über Autor(innen)

Xiao-Li Li is currently a principal investigator at the data mining department, 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 in 2001 from Chinese Academy of Sciences 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 the members 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 serving as an editorial board member for International Journal of Data Analysis Techniques and Strategies (IJDATS), Journal of Information Technology Research (JITR) and IGI editorial advisory review board. 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). See-Kiong Ng is currently the department head of the Data Mining Department at Institute for Infocomm Research. He is also an adjunct associate professor at the School of Computer Engineering, Nanyang Technological University. See-Kiong 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. See-Kiong'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.