Discovering biomolecular mechanisms with computational biology
Author(s)
Bibliographic Information
Discovering biomolecular mechanisms with computational biology
（Molecular biology intelligence unit）
Landes Bioscience/Eurekah.com , Springer Science+Business Media, c2006
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
Prediction of Post-translational modifications from amino acid sequence: Problems, pitfalls, methodological hints.- Deriving Biological Function of Genome Information with Biomolecular Sequence and Structure Analysis.- Reliable and Specific Protein Function Prediction by Combining Homology with Genomic(s) Context.- Clues from Three-Dimensional Structure Analysis and Molecular Modelling.- Prediction of Protein Function.- Complementing Biomolecular Sequence Analysis with Text Mining in Scientific Articles.- Extracting Information for Meaningful Function Inference through Text-Mining.- Literature and Genome Data Mining for Prioritizing Disease-Associated Genes.- Mechanistic Predictions from the Analysis of Biomolecular Networks.- Model-Based Inference of Transcriptional Regulatory Mechanisms from DNA Microarray Data.- The Predictive Power of Molecular Network Modelling.- Mechanistic Predictions from the Analysis of Biomolecular Sequence Populations: Considering Evolution for Function Prediction.- Theory of Early Molecular Evolution.- Hitchhiking Mapping.- Understanding the Functional Importance of Human Single Nucleotide Polymorphisms.- Correlations between Quantitative Measures of Genome Evolution, Expression and Function.
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