Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

by Marchiori, Elena; Moore, Jason H.; Rajapakse, Jagath Chandana

• ISBN13: 9783540717829
• ISBN10: 354071782X
• Format: Paperback
• Copyright: 2007-05-03
• Publisher: Springer-Verlag New York Inc

Summary

This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007, held in Valencia, Spain in April 2007, colocated with the Evo* 2007 events. The 28 revised full papers were carefully reviewed and selected from 60 submissions. Bringing experts in computer science together with experts in bioinformatics and the biological sciences resulted in contributions on fundamental and theoretical issues, along with a wide variety of papers dealing with different applications areas, such as biomarker discovery, cell simulation and modeling, ecological modeling, fluxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology

Table of Contents

Identifying regulatory sites using neighborhood species	p. 1
Genetic programming and other machine learning approaches to predict median oral lethal dose (LD[subscript 50]) and plasma protein binding levels (%PPB) of drugs	p. 11
Hypothesis testing with classifier systems for rule-based risk prediction	p. 24
Robust peak detection and alignment of nanoLC-FT mass spectrometry data	p. 35
One-versus-one and one-versus-au multiclass SVM-RFE for gene selection in cancer classification	p. 47
Understanding signal sequences with machine learning	p. 57
Targeting differentially co-regulated genes by multiobjective and multimodal optimization	p. 68
Modeling genetic networks : comparison of static and dynamic models	p. 78
A genetic embedded approach for gene selection and classification of microarray data	p. 90
Modeling the shoot apical meristem in A. thaliana : parameter estimation for spatial pattern formation	p. 102
Evolutionary search for improved path diagrams	p. 114
Simplifying amino acid alphabets using a genetic algorithm and sequence alignment	p. 122
Towards evolutionary network reconstruction tools for systems biology	p. 132
A Gaussian evolutionary method for predicting protein-protein interaction sites	p. 143
Bio-mimetic evolutionary reverse engineering of genetic regulatory networks	p. 155
Tuning reliefF for genome-wide genetic analysis	p. 166
Dinucleotide step parameterization of pre-miRNAs using multi-objective evolutionary algorithms	p. 176
Amino acid features for prediction of protein-protein interface residues with support vector machines	p. 187
Predicting HIV protease-cleavable peptides by discrete support vector machines	p. 197
Inverse protein folding on 2D off-lattice model : initial results and perspectives	p. 207
Virtual error : a new measure for evolutionary biclustering	p. 217
Characterising DNA/RNA signals with crisp hypermotifs : a case study on core promoters	p. 227
Evaluating evolutionary algorithms and differential evolution for the online optimization of fermentation processes	p. 236
The role of a priori information in the minimization of contact potentials by means of estimation of distribution algorithms	p. 247
Classification of cell fates with support vector machine learning	p. 258
Reconstructing linear gene regulatory networks	p. 270
Individual-based modeling of bacterial foraging with quorum sensing in a time-varying environment	p. 280
Substitution matrix optimisation for peptide classification	p. 291
Table of Contents provided by Blackwell. All Rights Reserved.