Artificial Intelligence and Heuristic Methods in Bioinformatics

by R. Shamir, P. Frasconi

Overview

The 14 papers consider how various methods in artificial intelligence are applied to problems in bioinformatics. Among the topics are statistical learning and kernel methods in bioinformatics, new machine learning methods for predicting protein topologies, multiple sequence alignments information in structure and function prediction, pattern discovery and the algorithms of surprise, the computational identification of regulatory sites in DNA sequences, computer system gene discovery for promoter structure analysis, and data acquisition and analysis in near-genome-wide expressions screening of tumor suppressor pathways using model cell lines with inducible transcription factors. There is no subject index. Annotation ©2004 Book News, Inc., Portland, OR

Product Details

ISBN-13:	9781586032944
Publisher:	IOS Press, Incorporated
Publication date:	01/01/2003
Series:	NATO Science Series
Pages:	256
Product dimensions:	9.66(w) x 6.54(h) x 0.82(d)

Table of Contents

	Preface	v
	Statistical Learning and Kernel Methods in Bioinformatics	1
	Neural Networks and the Prediction of Protein Structure	22
	Neural Networks Predict Protein Structure: Hype or Hit?	34
	New Machine Learning Methods for the Prediction of Protein Topologies	51
	Protein Folding using Contact Maps and Contact Vectors	75
	Multiple Sequence Alignments Information in Structure and Function Prediction	83
	Role Assignments: Bacterial Protein Families and Superfamilies	95
	Pattern Discovery and the Algorithmics of Surprise	111
	Techniques for Comparison, Pattern Matching and Pattern Discovery: From Sequences to Protein Topology	128
	Computational Identification of Regulatory Sites in DNA Sequences	148
	Computer System "Gene Discovery" for Promoter Structure Analysis	173
	Inductive Databases for Bio- and Chemo-Informatics	193
	Near Genome Wide Expression Screening of Tumor Suppressor Pathways using Model Cell Lines with Inducible Transcription Factors--Data Acquisition and Analysis	208
	Describing In-vitro Cell Proliferation and Transformation with Cellular Automata	224
	Author Index	243