10% off all books and free delivery over £50
Buy from our bookstore and 25% of the cover price will be given to a school of your choice to buy more books. *15% of eBooks.

An Introduction to Protein Informatics

View All Editions (2)

The selected edition of this book is not available to buy right now.
Add To Wishlist
Write A Review

About

An Introduction to Protein Informatics Synopsis

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.

About This Edition

ISBN: 9781461348399
Publication date:
Author: KarlHeinz Zimmermann
Publisher: Springer-Verlag New York Inc.
Format: Paperback
Pagination: 280 pages
Series: The Springer International Series in Engineering and Computer Science
Genres: Mathematical theory of computation
Information technology: general topics
Computational chemistry
Optimization
Probability and statistics

Frequently asked questions