Computational methods pertaining to many branches of science, such as physics, physical chemistry and biology, are presented. The text is primarily intended for third-year undergraduate or first-year graduate students. However, active researchers wanting to learn about the new techniques of computational science should also benefit from reading the book. It treats all major methods, including the powerful molecular dynamics method, Brownian dynamics and the Monte-Carlo method. All methods are treated equally from a theroetical point of view. In each case the underlying theory is presented and then practical algorithms are displayed, giving the reader the opportunity to apply these methods directly. For this purpose exercises are included. The book also features complete program listings ready for application.

Computational Genome Analysis

Computers & Technology

Waterman, Michael S.

Deonier, Richard C.

Tavaré, Simon

Computer Science

Springer

This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.

Computational Genome Analysis: An Introduction (Statistics for Biology & Health S)

Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.

Introduction to Computational Biology: Maps, Sequences and Genomes (Chapman & Hall/CRC Interdisciplinary Statistics)

Chapman and Hall/CRC

Mathl Methods for DNA Sequences

Science & Math

Biological Sciences

CRC-Press

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 Computational Biology: Maps, Sequences and Genomes, Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics)

Chen, Ting

Sun, Fengzhu

Computational Genome Analysis: An Introduction

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