Bioinformatics and Genome Analysis by H.-W. MewesBioinformatics and Genome Analysis by H.-W. Mewes

Bioinformatics and Genome Analysis

byH.-W. MewesEditorH. Seidel, B. Weiss

Paperback | December 26, 2012

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Bioinformatics is emerging as a field with ever-increasing promise, ur­ gency, and necessity. All three of these facets can be seen in the con­ text of the recent sequencing of the human genome. The creation of a novel algorithm for the assembly of whole genome shotgun data sets accelerated the project and resulted in its near completion in 2001. The urgency became apparent with the landslide of data that ensued and the realization that current databases and tool sets are not up to the task. Finally, the necessity of bioinformatics as a facet of molecular biologi­ cal research becomes evident in the impossibility of individual human comprehension of all the details of the functioning of a cell at the mo­ lecular level, especially now that we stand on the edge of this preci­ pice. We find ourselves at a time when we have the essentially complete genomes of human and mouse, and the completed sequences of Droso­ phila melanogaster, Caenorhabditis elegans, several fungi including Saccharomyces cerevisiae, and many bacteria including Escherichia coli. There are volumes of mRNA expression data sets, high-density maps of highly variable SNPs for both human and mouse, physical marker maps for many other important agricultural and drug trial ani­ mals, and a complete knock-out survey of yeast. In addition, the se­ quencing of D. pseudoobscura and Caenorhabditis briggsae in the near future will provide unusual comparative genomic insights.
Title:Bioinformatics and Genome AnalysisFormat:PaperbackDimensions:300 pagesPublished:December 26, 2012Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3662047497

ISBN - 13:9783662047491

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Table of Contents

1 Dissecting the Genetic Component of Complex Diseases in Humans.- 2 Bioinformatics of Membrane Proteins.- 3 SNAPping Up Functionally Related Genes Based on Context Information: A Colinearity-Free Approach.- 4 Promoter Analysis.- 5 Cluster Analysis and Its Applications to Gene Expression Data.- 6 Statistical Methods for Analyzing Gene Expression Data for Cancer Research.- 7 Comparing Secondary Structure 'Stick' Models of Proteins Using Graph Matching with Double Dynamic Programming.- 8 Computational Structural Proteomics.- 9 Proteomics in Biological Research: The Challenge to Make Proteins Speak.- 10 Construction and Prediction of Protein-Protein Interaction Maps.- 11 Bioinformatics, Cellular Flows, and Calculation.- 12 Graph-Based Analysis of Metabolic Networks.- 13 Orphan Protein Function and Its Relation to Glycosylation.- Previous Volumes Published in This Series.