2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008)

The success of Bioinformatics in recent years has been prompted by research in mole- lar biology and medicine in initiatives like the human genome project. The volume and diversification of data has increased so much that it is very hard if not impossible to analyze it by human experts. The analysis of this growing body of data, intensified by the development of a number of high-throughput experimental techniques that are generating the so called 'omics' data, has prompted for new computational methods. New global approaches, such as Systems Biology, have been emerging replacing the reductionist view that dominated biology research in the last decades, requiring the coordinated efforts of biological researchers with those related to data analysis, mathematical modelling and computer science. Computational methods have been helping in tasks related to knowledge discovery, modelling and optimization tasks. This workshop brings the opportunity to discuss applications of Bioinformatics and Computational Biology exploring the interactions between computer scientists, bio- gists and other scientific researchers. The IWPACBB technical program includes 29 papers (23 long papers and 6 short papers) selected from a submission pool of 51 papers, from 9 different countries. We thank the excellent work of the local organization members and also from the members of the Program Committee for their excellent reviewing work. October 2008 Juan M. Corchado Juan F. De Paz Miguel P. Rocha Florentino Fernández Riverola Organization

Table of Contents:
Applications.- Comparing Time Series through Event Clustering.- Visual Knowledge-Based Metaphors to Support the Analysis of Polysomnographic Recordings.- A Bio-inspired Proposal for Focus Attention While Preserving Information.- Modelling Fed-Batch Fermentation Processes: An Approach Based on Artificial Neural Networks.- Treatment and Diagnosis.- New Principles and Adequate Control Methods for Insulin Dosage in Case of Diabetes.- A Framework for CBR Development and Experimentation with Application to Medical Diagnosis.- Identification of Relevant Knowledge for Characterizing the Melanoma Domain.- TAT-NIDS: An Immune-Based Anomaly Detection Architecture for Network Intrusion Detection.- Genome.- Novel Computational Methods for Large Scale Genome Comparison.- Improving Literature Searches in Gene Expression Studies.- Implementing an Interactive Web-Based DAS Client.- Data Integration Issues in the Reconstruction of the Genome-Scale Metabolic Model of Zymomonas Mobillis.- Microarray 1.- Applying CBR Systems to Micro Array Data Classification.- Multiple-Microarray Analysis and Internet Gathering Information with Application for Aiding Medical Diagnosis in Cancer Research.- Evolutionary Techniques for Hierarchical Clustering Applied to Microarray Data.- Beds and Bits: The Challenge of Translational Bioinformatics.- Microarray 2.- A Matrix Factorization Classifier for Knowledge-Based Microarray Analysis.- Named Entity Recognition and Normalization: A Domain-Specific Language Approach.- BIORED - A Genetic Algorithm for Pattern Detection in Biosequences.- A Recursive Genetic Algorithm to Automatically Select Genes for Cancer Classification.- Proteins and Cells.- On Mining Protein Unfolding Simulation Data with Inductive Logic Programming.- A Knowledge Discovery Method for the Characterization of Protein Unfolding Processes.- Design of New Chemoinformatic Tools for the Analysis of Virtual Screening Studies: Application to Tubulin Inhibitors.- Multi-Objective Optimization of Biological Networks for Prediction of Intracellular Fluxes.- Mathematical Models.- SimSearch: A New Variant of Dynamic Programming Based on Distance Series for Optimal and Near-Optimal Similarity Discovery in Biological Sequences.- Tuning Parameters of Evolutionary Algorithms Using ROC Analysis.- Speeding-Up ACO Implementation by Decreasing the Number of Heuristic Function Evaluations in Feature Selection Problem.- Global Sensitivity Analysis of a Biochemical Pathway Model.- Improving a Leaves Automatic Recognition Process Using PCA.