Discovering Biomolecular Mechanisms with Computational Biology

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 Biol...

Full description

Saved in:
Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Eisenhaber, Frank. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Format: Electronic eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 2006.
Edition:1st ed. 2006.
Series:Molecular Biology Intelligence Unit,
Subjects:
Online Access:https://doi.org/10.1007/0-387-36747-0
Tags: Add Tag
No Tags, Be the first to tag this record!
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.