Protein informatics is a newer name for an already existing discipline. It encompasses the techniques used in bioinformatics and molecular modeling that are related to proteins. While bioinformatics is mainly concerned with the collection, organization, and analysis of biological data, molecular modeling is devoted to representation and manipulation of the structure of proteins.

Protein informatics requires substantial prerequisites on computer science, mathematics, and molecular biology. The approach chosen here, allows a direct and rapid grasp on the subject starting from basic knowledge of algorithm design, calculus, linear algebra, and probability theory.

An Introduction to Protein Informatics , a professional monograph will provide the reader a comprehensive introduction to the field of protein informatics. The text emphasizes mathematical and computational methods to tackle the central problems of alignment, phylogenetic reconstruction, and prediction and sampling of protein structure.

An Introduction to Protein Informatics is designed for a professional audience, composed of researchers and practitioners within bioinformatics, molecular modeling, algorithm design, optimization, and pattern recognition. This book is also suitable as a graduate-level text for students in computer science, mathematics, and biomedicine.

Autorentext

Dr. Karl-Heinz Zimmermann studierte Informatik und Mathematik an der Universität Erlangen-Nürnberg. Er promovierte dort in Theoretischer Informatik und habilitierte in Mathematik an der Universität Bayreuth. Er war Fulbright-Stipendiat an der Princeton Universität und Heisenberg-Stipendiat an der Universität Karlsruhe (TH). Er ist seit 25 Jahren Professor für Informatik an der Technischen Universität Hamburg und Autor von mehreren Forschungsmonographien sowie von über 120 wissenschaftlichen Forschungspublikationen.

Inhalt

1. Proteins.- 2. Biosynthesis.- 3. Pairwise Sequence Alignment.- 4. Multiple Sequence Alignment.- 5. Phylogenetic Trees.- 6. Secondary Structure Prediction.- 7. Tertiary Structure Prediction.- 8. Stochastic Sampling Methods.- Appendices.- A The List of Considered Proteins.- B Rost-Sander Set.- C Substitution Matrices.- References.