Discovering Biomolecular Mechanisms with  Computational Biology by Frank EisenhaberDiscovering Biomolecular Mechanisms with  Computational Biology by Frank Eisenhaber

Discovering Biomolecular Mechanisms with Computational Biology

EditorFrank Eisenhaber

Hardcover | June 13, 2006

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This anthology presents critical reviews of methods and high-impact applications in computational biology that lead to results that non-bioinformaticians must also know to design efficient experimental research plans. Discovering Biomolecular Mechanisms with Computational Biology explores the methodology of translating sequence strings into biological knowledge and considers exemplary groundbreaking results such as unexpected enzyme discoveries. This book also summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation.
Title:Discovering Biomolecular Mechanisms with Computational BiologyFormat:HardcoverDimensions:158 pages, 9.25 × 6.1 × 0 inPublished:June 13, 2006Publisher:Springer USLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0387345272

ISBN - 13:9780387345277

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Table of Contents

Reliable and Specific Protein Function Prediction by Combining Homology with Genomic(s) Context.- Clues from Three-Dimensional Structure Analysis and Molecular Modelling: New Insights into Cytochrome P450 Mechanisms and Functions.- Prediction of Protein Function: Two Basic Concepts and One Practical Recipe.- Extracting Information for Meaningful Function Inference through Text-Mining.- Literature and Genome Data Mining for Prioritizing Disease-Associated Genes.- Model-Based Inference of Transcriptional Regulatory Mechanisms from DNA Microarray Data.- The Predictive Power of Molecular Network Modelling: Case Studies of Predictions with Subsequent Experimental Verification.- Theory of Early Molecular Evolution: Predictions and Confirmations.- Hitchhiking Mapping: Limitations and Potential for the Identification of Ecologically Important Genes.- Understanding the Functional Importanceof Human Single Nucleotide Polymorphisms.- Correlations between Quantitative Measures of Genome Evolution, Expression and Function.- Index.