Advances in Bioinformatics [electronic resource] : 4th International Workshop on Practical Applications of Computational Biology and Bioinformatics 2010 (IWPACBB 2010) /
International Workshop on Practical Applications of Computational Biology and BioinformaticsCorporate Author
International Workshop on Practical Applications of Computational Biology and Bioinformatics.
International Workshop on Practical Applications of Computational Biology and Bioinformatics
Rocha, Miguel P.editor.
Fernández Riverola, Florentino.editor.
Shatkay, Hagit.editor.
Corchado Rodríguez, Juan Manuel.editor.
The fields of Bioinformatics and Computational Biology have been growing steadily over the last few years boosted by an increasing need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology. This calls for new algorithms and approaches from fields such as Data Integration, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence.
Description based upon print version of record.
Includes bibliographical references and index.
Microarrays -- Highlighting Differential Gene Expression between Two Condition Microarrays through Heterogeneous Genomic Data: Application to Lesihmania infantum Stages Comparison -- An Experimental Evaluation of a Novel Stochastic Method for Iterative Class Discovery on Real Microarray Datasets -- Automatic Workflow during the Reuse Phase of a CBP System Applied to Microarray Analysis -- A Comparative Study of Microarray Data Classification Methods Based on Ensemble Biological Relevant Gene Sets -- Data Mining and Data Integration -- Predicting the Start of Protein ?-Helices Using Machine Learning Algorithms -- A Data Mining Approach for the Detection of High-Risk Breast Cancer Groups -- GRASP for Instance Selection in Medical Data Sets -- Expanding Gene-Based PubMed Queries -- Improving Cross Mapping in Biomedical Databases -- An Efficient Multi-class Support Vector Machine Classifier for Protein Fold Recognition -- Feature Selection Using Multi-Objective Evolutionary Algorithms: Application to Cardiac SPECT Diagnosis -- Phylogenetics and Sequence Analysis -- Two Results on Distances for Phylogenetic Networks -- Cramér Coefficient in Genome Evolution -- An Application for Studying Tandem Repeats in Orthologous Genes -- Accurate Selection of Models of Protein Evolution -- Scalable Phylogenetics through Input Preprocessing -- The Median of the Distance between Two Leaves in a Phylogenetic Tree -- In Silico AFLP: An Application to Assess What Is Needed to Resolve a Phylogeny -- Employing Compact Intra-genomic Language Models to Predict Genomic Sequences and Characterize Their Entropy -- Biomedical Applications -- Structure Based Design of Potential Inhibitors of Steroid Sulfatase -- Agent-Based Model of the Endocrine Pancreas and Interaction with Innate Immune System -- State-of-the-Art Genetic Programming for Predicting Human Oral Bioavailability of Drugs -- Pharmacophore-Based Screening as a Clue for the Discovery of New P-Glycoprotein Inhibitors -- Bioinformatics Applications -- e-BiMotif: Combining Sequence Alignment and Biclustering to Unravel Structured Motifs -- Applying a Metabolic Footprinting Approach to Characterize the Impact of the Recombinant Protein Production in Escherichia coli -- Rbbt: A Framework for Fast Bioinformatics Development with Ruby -- Analysis of the Effect of Reversibility Constraints on the Predictions of Genome-Scale Metabolic Models -- Enhancing Elementary Flux Modes Analysis Using Filtering Techniques in an Integrated Environment -- Genome Visualization in Space -- A Hybrid Scheme to Solve the Protein Structure Prediction Problem.
The fields of Bioinformatics and Computational Biology have been growing steadily over the last few years boosted by an increasing need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology. This calls for new algorithms and approaches from fields such as Data Integration, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence.
Bioinformatics.
Computational intelligence.
Artificial intelligence.
Bioinformatics.
Computational Biology/Bioinformatics.
Computational Intelligence.
Artificial Intelligence.
Advances in Intelligent and Soft Computing