Marchiori / Rajapakse / Moore | Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics | Buch | 978-3-540-71782-9 | sack.de

Buch, Englisch, Band 4447, 302 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 487 g

Reihe: Lecture Notes in Computer Science

Marchiori / Rajapakse / Moore

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

5th European Conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007, Proceedings
2007
ISBN: 978-3-540-71782-9
Verlag: Springer Berlin Heidelberg

5th European Conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007, Proceedings

Buch, Englisch, Band 4447, 302 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 487 g

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-540-71782-9
Verlag: Springer Berlin Heidelberg


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, April 2007. Coverage brings together experts in computer science with experts in bioinformatics and the biological sciences. It presents contributions on fundamental and theoretical issues along with papers dealing with different applications areas.

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Weitere Infos & Material


Identifying Regulatory Sites Using Neighborhood Species.- Genetic Programming and Other Machine Learning Approaches to Predict Median Oral Lethal Dose (LD50) and Plasma Protein Binding Levels (%PPB) of Drugs.- Hypothesis Testing with Classifier Systems for Rule-Based Risk Prediction.- Robust Peak Detection and Alignment of nanoLC-FT Mass Spectrometry Data.- One-Versus-One and One-Versus-All Multiclass SVM-RFE for Gene Selection in Cancer Classification.- Understanding Signal Sequences with Machine Learning.- Targeting Differentially Co-regulated Genes by Multiobjective and Multimodal Optimization.- Modeling Genetic Networks: Comparison of Static and Dynamic Models.- A Genetic Embedded Approach for Gene Selection and Classification of Microarray Data.- Modeling the Shoot Apical Meristem in A. thaliana: Parameter Estimation for Spatial Pattern Formation.- Evolutionary Search for Improved Path Diagrams.- Simplifying Amino Acid Alphabets Using a Genetic Algorithm and Sequence Alignment.- Towards Evolutionary Network Reconstruction Tools for Systems Biology.- A Gaussian Evolutionary Method for Predicting Protein-Protein Interaction Sites.- Bio-mimetic Evolutionary Reverse Engineering of Genetic Regulatory Networks.- Tuning ReliefF for Genome-Wide Genetic Analysis.- Dinucleotide Step Parameterization of Pre-miRNAs Using Multi-objective Evolutionary Algorithms.- Amino Acid Features for Prediction of Protein-Protein Interface Residues with Support Vector Machines.- Predicting HIV Protease-Cleavable Peptides by Discrete Support Vector Machines.- Inverse Protein Folding on 2D Off-Lattice Model: Initial Results and Perspectives.- Virtual Error: A New Measure for Evolutionary Biclustering.- Characterising DNA/RNA Signals with Crisp Hypermotifs: A Case Study on Core Promoters.-Evaluating Evolutionary Algorithms and Differential Evolution for the Online Optimization of Fermentation Processes.- The Role of a Priori Information in the Minimization of Contact Potentials by Means of Estimation of Distribution Algorithms.- Classification of Cell Fates with Support Vector Machine Learning.- Reconstructing Linear Gene Regulatory Networks.- Individual-Based Modeling of Bacterial Foraging with Quorum Sensing in a Time-Varying Environment.- Substitution Matrix Optimisation for Peptide Classification.



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