Problem Solving Handbook in Computational Biology and Bioinformatics / edited by Lenwood S. Heath, Naren Ramakrishnan.

Format:

Book

Contributor:

Heath, Lenwood S. (Lenwood Scott), editor.

Ramakrishnan, Naren, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Language:

English

Subjects (All):

Bioinformatics.

Algorithms.

Computational Biology/Bioinformatics.

Algorithm Analysis and Problem Complexity.

Local Subjects:

Computational Biology/Bioinformatics.

Algorithm Analysis and Problem Complexity.

Bioinformatics.

Physical Description:

1 online resource (XVII, 347 pages)

Edition:

First edition 2011.

Contained In:

Springer eBooks

Place of Publication:

New York, NY : Springer US : Imprint: Springer, 2011.

System Details:

text file PDF

Summary:

Bioinformatics is growing by leaps and bounds; theories/algorithms/statistical techniques are constantly evolving. Nevertheless, a core body of algorithmic ideas have emerged and researchers are beginning to adopt a "problem solving" approach to bioinformatics, wherein they use solutions to well-abstracted problems as building blocks to solve larger scope problems. Problem Solving Handbook for Computational Biology and Bioinformatics is an edited volume contributed by world renowned leaders in this field. This comprehensive handbook with problem solving emphasis, covers all relevant areas of computational biology and bioinformatics. Web resources and related themes are highlighted at every opportunity in this central easy-to-read reference. Designed for advanced-level students, researchers and professors in computer science and bioengineering as a reference or secondary text, this handbook is also suitable for professionals working in this industry.

Contents:

Preface

Pairwise Sequence Alignment

Sequence and Sequence Alignment Statistics

Practical Multiple Sequence Alignment

Phylogenetic Trees from Sequences

Phylogenetic Networks

Modern BLAST Programs

Stochastic Calculus and Stochastic Simulation

Genomic Sequence Comparison

Genome Rearrangements

Population Genetics Data Analysis

Genome Wide Association Studies

Practical Implications of Coalescent Theory

Networks in Computational Systems Biology

Practical Use of the Gene Ontology

Techniques for Protein Structure

Microarray Experiment Statistics

Reasoning with Protein Contact Maps

Identifying Modules in Protein-Protein Interaction Networks

Motifs for Transcriptional Regulation

Time Course Analysis

Computational Simulation of Biochemical Networks

Biomedical Data Integration

Functional Annotation and Discovery

Matrix and Tensor Decompositions

Text Processing and Mining

Formal Logics

Index.

Other Format:

Printed edition:

ISBN:

978-0-387-09760-2

9780387097602

Access Restriction:

Restricted for use by site license.