Problem Solving Handbook in Computational Biology and Bioinformatics

Häftad, Engelska, 2014

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Beskrivning

Bioinformatics is constantly evolving, but a core body of algorithmic ideas for a problem-solving approach in the field has emerged. This handbook stresses that approach as it covers all relevant areas of computational biology and bioinformatics.

Produktinformation

Utgivningsdatum:2014-08-15
Mått:155 x 235 x 20 mm
Vikt:557 g
Format:Häftad
Språk:Engelska
Antal sidor:347
Upplaga:2011
Förlag:Springer-Verlag New York Inc.
ISBN:9781489973481

Utforska kategorier

Hälsoinformatik inom Medicin
Medicinsk utrustning och medicinska tekniker inom Medicin
Biovetenskap inom Naturvetenskap och teknik

Recensioner i media

From the reviews: "The editors of this handbook ... have 'collect(ed) together, in one place, the algorithms and methods that form the modern bioinformatician's toolkit.' ... Each chapter contains an introduction to the respective topic, detailed descriptions of the relevant algorithmic methods, software implementations, and applications, and concludes with advanced topics. ... this handbook provides some value for researchers and practitioners in the field. ... In summary, for most of the topics covered, this book complements the standard textbooks in a useful way." (Gunnar Klau, ACM Computing Reviews, June, 2011)

Innehållsförteckning

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.