Function Annotation in Gene Networks



Modern sequencing technology enables the discovery of new gene products in an increasing number of organisms. However, the sequence on its own does not provide sufficient information about cellular mechanisms and their function. Efforts need to be directed toward genome characterization at the molecular level. Wet-lab experiments in this direction are assisted by a variety of computational methods that exploit the abundance of data. The advent of high-throughput interaction detection methods has generated large amounts of gene interaction data. This has allowed the construction of genome-wide networks. Studying genomes in a networked setting has been beneficial for global annotation in two ways. First, there has been an increasing number of network-based function prediction methods. Second, networks have inspired the community to revisit the definition of gene function. The original molecular characterization of function has been extended to a multi-molecule function, termed biological process[Gene ontology: Tool for the unification of biology. Nature, 2000] in recently emerging annotation systems. In this chapter, we present the current methods of automated annotation of protein functions. We describe existing annotation prediction methods and ontologies used to define a gene’s function at the molecular and process level. We discuss in detail the workings of a generalized framework for network prediction and present experimental accuracy comparison of several popular methods within this framework. We also discuss the use of networks from multiple species for annotation enrichment in sparse genomes.



This material is based upon work supported by the National Science Foundation under Grant No. IIS-0917149.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Petko Bogdanov
    • 1
  • Kathy Macropol
    • 2
  • Ambuj K. Singh
    • 3
  1. 1.Department of Computer ScienceUniversity of CaliforniaSanta BarbaraUSA
  2. 2.University of California, Santa BarbaraSanta BarbaraUSA
  3. 3.University of CaliforniaSanta BarbaraUSA

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