Introduction to Computational Biology
Maps, Sequences and Genomes, Second Edition
By Michael S. Waterman, Ting Chen, Fengzhu Sun
To Be Published February 15th 2014 by Chapman and Hall/CRC – 576 pages
To Be Published February 15th 2014 by Chapman and Hall/CRC – 576 pages
This second edition is aimed at researchers and graduate students in the quantitative sciences needing an introduction to the application of mathematical, statistical and computational methods in molecular biology. It is well known for the quality of the exposition and the perfect balance of mathematical theory and biological aspects. The text includes the necessary mathematical details with lots of detailed real examples, without overburdening the reader with unnecessary proofs and formalisms. This new edition has been substantially updated and now includes new chapters on genome rearrangements, motif finding, gene prediction, gene and protein networks and future research directions.
Introduction to Biology
Problem Formulation and Restriction Maps
Algorithms and Analyzing Maps
Physical Genome Maps: Oceans, Islands and Anchol's
Sequence Assembly
Fast Sequence Comparison and Database Search
Dynamic Programming for Pairwise Alignments
Multiple Sequence Alignments
Genome Rearrangements
RNA Secondary Structures
Probability and Statistics for Sequence Alignment
Probability and Statistics for Sequence Patterns
Statistical Methods for Motif Finding
Trees and Sequences
Gene Prediction
Analysis of Gene and Protein Networks
Perspectives and Future
Michael S. Waterman, Ting Chen, and Fengzhu Sun are with the Departments of Biology, Computer Science and Mathematics at the University of Southern California, USA.
Name: Introduction to Computational Biology: Maps, Sequences and Genomes, Second Edition (Hardback) – Chapman and Hall/CRC
Description: By Michael S. Waterman, Ting Chen, Fengzhu Sun. This second edition is aimed at researchers and graduate students in the quantitative sciences needing an introduction to the application of mathematical, statistical and computational methods in molecular biology. It is well known for the quality of the...
Categories: Bioinformatics