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Sequence Analysis of Protein Domains Workshops

In May this year, the EBI and Sanger Centre held two workshops on the analysis of protein domains in sequences. The first workshop was held for participants from the pharmaceutical and biotech industries of the EBI's Industry Programme, the second was for delegates from academic and research institutes, and was funded partly by the Wellcome Trust.

The characterisation and analysis of protein domains is a recurrent theme in all branches of molecular biology, from structure determination through to making sense of human disease genes. There have been many recent advances in the theory and practice of sequence analysis, in particular for protein domains. This has led to many new programs and resources being available to the researcher.

However, even motivated biologists with good sequence analysis skills are not exposed to all the new methods since these are often not reported in the mainstream biology literature. The workshops aimed to train experimental biologists and computer scientists in current sequence analysis techniques by communicating expert knowledge to allow researchers to raise their level of expertise in this field, and provide a strong practical grounding in the methods.

The emphasis of the courses was on the application of Hidden Markov Models (HMMs) in sequence analysis. The theory of HMMs allows one to design mathematical models of biological systems, based on a collection of observations of those systems. The strength of HMMs is the possibility to derive understandable rules, with a highly accurate predictive power for detecting instances of the system studied, from the generated models.

The workshops focused on defining, discovering and using protein domain information. The course content was designed for biologists and computer scientists who wanted to extend their sequence analysis skills to cover domain-hunting techniques and included: How to spot a domain from single sequence searches; How to find all the members and develop an effective multiple alignment; How to use the multiple alignment in profile-HMM searches; How to use the multiple alignment for secondary structure prediction.

Each course lasted three days. The morning was split into seminars on the theoretical and practical aspects of the problem. The afternoon was devoted to a practical session. In the evenings, there was a research-orientated seminar where one of the tutors presented his or her work to the participants.

Tutors participating in the workshop included: Tim Hubbard (Sanger Centre), Alex Bateman (Sanger Centre), Joerg Schultz (EMBL Heidelberg), Richard Durbin (Sanger Centre), Sarah Teichman (LMB, Cambridge), Geoff Barton (EBI), and Ewan Birney (Sanger Centre).

The organisers of the workshop were Ewan Birney (Sanger Centre), Alex Bateman (Sanger Centre) and Alan Robinson (EBI).

Article by: Alan Robinson


 

Resources and further information

  • European Bioinformatics Institute (EMBL-EBI)
    http://www.ebi.ac.uk/
  • The Sanger Centre
    http://www.sanger.ac.uk/
    • Pfam - Protein families database of alignments and HMMs. Pfam is a large collection of multiple sequence alignments and hidden Markov models covering many common protein domains.
      http://www.sanger.ac.uk/Software/Pfam/
  • Washington University in St. Louis (USA)
    http://www.wustl.edu/
    • HMMER 2.0 - HMMER is a freely distributable implementation of profile HMM software for protein sequence analysis. Profile hidden Markov models (profile HMMs) can be used to do sensitive database searching using statistical descriptions of a sequence family's consensus.
      http://hmmer.wustl.edu/
  • The Wellcome Trust
    http://www.wellcome.ac.uk/

 

External sites are not endorsed by EMBL-EBI

 

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