Bioinformation Discovery: Data to Knowledge in Biology

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Bioinformation Discovery illustrates the power of biological data in knowledge discovery. It describes biological data types and representations with examples for creating a workflow in Bioinformation discovery. The concepts in knowledge discovery from data are illustrated using line diagrams. The principles and concepts in knowledge discovery are used for the development of prediction models for simulations of biological reactions and events. Advanced topics in molecular evolution and cellular & molecular biology are addressed using Bioinformation gleaned through discovery. Each chapter contains approximately 10 exercises for practice. This will help students to expand their problem solving skills in Bioinformation Discovery. Each chapter concludes with a number of good problem sets to test mastery of the material.

Author(s): Pandjassarame Kangueane (auth.)
Edition: 1
Publisher: Springer-Verlag New York
Year: 2009

Language: English
Pages: 166
Tags: Bioinformatics; Computational Biology/Bioinformatics; Immunology; Vaccine; Protein Structure

Front Matter....Pages i-xxv
Introduction....Pages 1-26
Creating Datasets....Pages 27-64
Tools and Techniques....Pages 65-77
Protein Subunits Interaction....Pages 79-86
Homodimer Folding and Binding....Pages 87-96
Fusion Proteins....Pages 97-110
Major Histocompatibility Complex (MHC) and Peptide Binding....Pages 111-130
HLA Supertypes....Pages 131-139
T-Epitope Designer....Pages 141-147
Eukaryotic Genes, Functions, Genomes, Design, and Evolution....Pages 149-162
Back Matter....Pages 163-166