Chapter 2. Knowledge-Driven Approaches to Genome-Scale Analysis

  1. Gil Alterovitz and
  2. Marco Ramoni
  1. Hannah Tipney and
  2. Lawrence Hunter

Published Online: 7 JUL 2010

DOI: 10.1002/9780470669716.ch2

Knowledge-Based Bioinformatics: From Analysis to Interpretation

Knowledge-Based Bioinformatics: From Analysis to Interpretation

How to Cite

Tipney, H. and Hunter, L. (2010) Knowledge-Driven Approaches to Genome-Scale Analysis, in Knowledge-Based Bioinformatics: From Analysis to Interpretation (eds G. Alterovitz and M. Ramoni), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470669716.ch2

Editor Information

  1. Harvard Medical School and Massachusetts Institute of Technology, Boston, USA

Author Information

  1. University of Colorado Denver, School of Medicine, USA

Publication History

  1. Published Online: 7 JUL 2010
  2. Published Print: 16 JUL 2010

ISBN Information

Print ISBN: 9780470748312

Online ISBN: 9780470669716

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Keywords:

  • 3R systems;
  • Accelerated biomedical discovery;
  • Ambiguity - linguistic;
  • Annotation - manual/automatic;
  • Artificial Intelligence;
  • Asymmetric co-occurrence fraction (ACF);
  • BioCreative;
  • Biomedical literature;
  • Biomedical text mining;
  • Co-occurrence - annotation terms;
  • Co-occurrence - literature;
  • Combined network;
  • Consensus reliability estimate;
  • Curation;
  • Cytoscape;
  • Cytoscape Plug-Ins - CommonAttributes/HiderSlider;
  • Data network;
  • Data reliability;
  • Database integration;
  • DAVID;
  • DIP;
  • Direct relationship;
  • Edge/Arc weight/Reliability;
  • Enrichment;
  • Explicit relationship;
  • Expression data;
  • GenBank;
  • Gene lists;
  • Gene Ontology (GO);
  • Gene Set Enrichment Analysis (GSEA);
  • Gene sets;
  • Genome-scale science;
  • Genomics;
  • Genotype-phenotype association;
  • GO term enrichment;
  • Gold Standard Dataset;
  • GWAS;
  • Hanalyzer;
  • High-throughput;
  • Homology;
  • Hypothesis generation;
  • Implicit knowledge;
  • Implicit relationship;
  • Implied knowledge;
  • Indirect relationship;
  • Inference - reasoning;
  • Inferred knowledge;
  • Information extraction;
  • Information retrieval;
  • Interaction prediction;
  • Interologs;
  • InterPro;
  • iRefWeb;
  • KEGG;
  • Knowledge driven investigations;
  • Knowledge extraction;
  • Knowledge integration;
  • Knowledge interaction;
  • Knowledge network;
  • Knowledge source reliability;
  • Microarray;
  • Model-based - reasoning;
  • Narration - reasoning;
  • Natural Language Processing (NLP);
  • Network biology;
  • Network combination metrics - Average/Hanisch Logit;
  • Network generation;
  • North American Association for Computational Linguistics;
  • Online Mendelian Inheritance in Man (OMIM);
  • Ontologies;
  • OpenDMAP;
  • Orthology;
  • Over-representation;
  • Pattern-based;
  • Protein-protein interaction;
  • Protein-protein interaction networks;
  • Proteomics;
  • Provenance;
  • PubMed;
  • Reading, reasoning and reporting;
  • Reasoning;
  • STRING;
  • Sub-network identification;
  • Systems Biology;
  • TREC;
  • Uncertainty;
  • Visual representation;
  • Visualization of knowledge/of information;
  • Yeast protein-protein interaction network

Summary

This chapter contains sections titled:

  • Fundamentals

  • Challenges in knowledge-driven approaches

  • Current knowledge-based bioinformatics tools

  • 3R systems: reading, reasoning and reporting the way towards biomedical discovery

  • The Hanalyzer: a proof of 3R concept

  • Acknowledgements

  • References