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Related Experiment Videos

Computer-assisted protein domain boundary prediction using the DomPred server.

Kevin Bryson1, Domenico Cozzetto, David T Jones

  • 1Department of Computer Science, University College London, Gower Street, London WC1E 6BT, United Kingdom.

Current Protein & Peptide Science
|April 14, 2007
PubMed
Summary
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Predicting protein domains from sequence is difficult. This study introduces the DomPred server, offering computer-assisted domain prediction to improve accuracy by combining multiple methods and expert knowledge.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Structural Bioinformatics

Background:

  • Protein domain prediction from sequence alone is a challenging task with diverse methodologies.
  • Complete automation of domain prediction faces limitations due to inherent difficulties and expert disagreement.
  • Human expert consensus on domain assignment is often required, highlighting the complexity of the problem.

Purpose of the Study:

  • To categorize diverse protein domain prediction methodologies.
  • To propose computer-assisted domain prediction as a more achievable goal.
  • To introduce and benchmark the DomPred server for enhanced domain prediction.

Main Methods:

  • Classification of existing domain prediction approaches into broad categories.

Related Experiment Videos

  • Benchmarking of two distinct methods (DPS and DomSSEA) implemented in the DomPred server.
  • Utilizing benchmark datasets with high human expert agreement for method evaluation.

    • Main Results:

    • Automatic structure-based domain assignment still shows disagreement even on expert-agreed datasets.
    • The DomPred server integrates two different categories of prediction methods (DPS and DomSSEA).
    • Individual benchmarking of methods provides reliability information using various scores relevant to prediction types.

    Conclusions:

    • Computer-assisted domain prediction is a more realistic and achievable objective than fully automatic methods.
    • The DomPred server facilitates user-guided domain prediction by offering multiple results and alternative suggestions.
    • The server empowers users to integrate their expertise with computational predictions for final domain assignment.