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In this anthology, leading researchers present critical reviews of methods and high-impact applications in computational biology that lead to results that also non-bioinformaticians must know to design efficient experimental research plans. Discovering Biomolecular Mechanisms with Computational Biology also summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation.
Discovering Biomolecular Mechanisms with Computational Biology is essential reading for life science researchers and higher-level students that work on biomolecular mechanisms and wish to understand the impact of computational biology for their success.
List 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.
Summary
In this anthology, leading researchers present critical reviews of methods and high-impact applications in computational biology that lead to results that also non-bioinformaticians must know to design efficient experimental research plans. Discovering Biomolecular Mechanisms with Computational Biology also summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation.
Discovering Biomolecular Mechanisms with Computational Biology is essential reading for life science researchers and higher-level students that work on biomolecular mechanisms and wish to understand the impact of computational biology for their success.
