EvoBIO 2007: Valencia, Spain

• Claudia Angelini, Luisa Cutillo, Italia De Feis, Richard C. van der Wath, Pietro Liò:
  Identifying Regulatory Sites Using Neighborhood Species. 1-10
  
• Francesco Archetti, Stefano Lanzeni, Enza Messina, Leonardo Vanneschi:
  Genetic Programming and Other Machine Learning Approaches to Predict Median Oral Lethal Dose (LD₅₀) and Plasma Protein Binding Levels (%PPB) of Drugs. 11-23
  
• Flavio Baronti, Antonina Starita:
  Hypothesis Testing with Classifier Systems for Rule-Based Risk Prediction. 24-34
  
• Marius C. Codrea, Connie R. Jimenez, Sander Piersma, Jaap Heringa, Elena Marchiori:
  Robust Peak Detection and Alignment of nanoLC-FT Mass Spectrometry Data. 35-46
  
• Kaibo Duan, Jagath C. Rajapakse, Minh Ngoc Nguyen:
  One-Versus-One and One-Versus-All Multiclass SVM-RFE for Gene Selection in Cancer Classification. 47-56
  
• Jean-Luc Falcone, Renée Kreuter, Dominique Belin, Bastien Chopard:
  Understanding Signal Sequences with Machine Learning. 57-67
  
• Oscar Harari, Cristina Rubio-Escudero, Igor Zwir:
  Targeting Differentially Co-regulated Genes by Multiobjective and Multimodal Optimization. 68-77
  
• Cristina Rubio-Escudero, Oscar Harari, Oscar Cordón, Igor Zwir:
  Modeling Genetic Networks: Comparison of Static and Dynamic Models. 78-89
  
• Jose Crispin Hernandez Hernandez, Béatrice Duval, Jin-Kao Hao:
  A Genetic Embedded Approach for Gene Selection and Classification of Microarray Data. 90-101
  
• Tim Hohm, Eckart Zitzler:
  Modeling the Shoot Apical Meristem in A. thaliana : Parameter Estimation for Spatial Pattern Formation. 102-113
  
• Kim Laurio, Thomas Svensson, Mats Jirstrand, Patric Nilsson, Jonas Gamalielsson, Björn Olsson:
  Evolutionary Search for Improved Path Diagrams. 114-121
  
• Jacek Lenckowski, Krzysztof Walczak:
  Simplifying Amino Acid Alphabets Using a Genetic Algorithm and Sequence Alignment. 122-131
  
• Thorsten Lenser, Thomas Hinze, Bashar Ibrahim, Peter Dittrich:
  Towards Evolutionary Network Reconstruction Tools for Systems Biology. 132-142
  
• Kang-Ping Liu, Jinn-Moon Yang:
  A Gaussian Evolutionary Method for Predicting Protein-Protein Interaction Sites. 143-154
  
• Daniel Marbach, Claudio Mattiussi, Dario Floreano:
  Bio-mimetic Evolutionary Reverse Engineering of Genetic Regulatory Networks. 155-165
  
• Jason H. Moore, Bill C. White:
  Tuning ReliefF for Genome-Wide Genetic Analysis. 166-175
  
• Jin-Wu Nam, In-Hee Lee, Kyu Baek Hwang, Seong-Bae Park, Byoung-Tak Zhang:
  Dinucleotide Step Parameterization of Pre-miRNAs Using Multi-objective Evolutionary Algorithms. 176-186
  
• Minh Ngoc Nguyen, Jagath C. Rajapakse, Kaibo Duan:
  Amino Acid Features for Prediction of Protein-Protein Interface Residues with Support Vector Machines. 187-196
  
• Carlotta Orsenigo, Carlo Vercellis:
  Predicting HIV Protease-Cleavable Peptides by Discrete Support Vector Machines. 197-206
  
• David A. Pelta, Alberto Carrascal:
  Inverse Protein Folding on 2D Off-Lattice Model: Initial Results and Perspectives. 207-216
  
• Beatriz Pontes, Federico Divina, Raúl Giráldez, Jesús S. Aguilar-Ruiz:
  Virtual Error: A New Measure for Evolutionary Biclustering. 217-226
  
• Carey Pridgeon, David Corne:
  Characterising DNA/RNA Signals with Crisp Hypermotifs: A Case Study on Core Promoters. 227-235
  
• Miguel Rocha, José P. Pinto, Isabel Rocha, Eugénio C. Ferreira:
  Evaluating Evolutionary Algorithms and Differential Evolution for the Online Optimization of Fermentation Processes. 236-246
  
• Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
  The Role of a Priori Information in the Minimization of Contact Potentials by Means of Estimation of Distribution Algorithms. 247-257
  
• Ofer M. Shir, Vered Raz, Roeland W. Dirks, Thomas Bäck:
  Classification of Cell Fates with Support Vector Machine Learning. 258-269
  
• Jochen Supper, Christian Spieth, Andreas Zell:
  Reconstructing Linear Gene Regulatory Networks. 270-279
  
• W. J. Tang, Q. H. Wu, J. R. Saunders:
  Individual-Based Modeling of Bacterial Foraging with Quorum Sensing in a Time-Varying Environment. 280-290
  
• David C. Trudgian, Zheng Rong Yang:
  Substitution Matrix Optimisation for Peptide Classification. 291-300