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Classification of proteins by sequence signatures

Part 3. Proteomics

3.6. Proteome Families

Basic Techniques and Approaches

  1. Kay Hofmann

Published Online: 15 OCT 2004

DOI: 10.1002/047001153X.g306406

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Hofmann, K. 2004. Classification of proteins by sequence signatures. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 3:3.6:91.

Author Information

  1. Memorec Biotec GmbH, Köln, Germany

Publication History

  1. Published Online: 15 OCT 2004

Abstract

The prediction of a protein's function from its amino acid sequence is one of the most important tasks in bioinformatics. The traditional procedure of searching databases for related sequences and inferring the function from the best matches has several shortcomings and pitfalls. Alternatively, the sequence under study can be scrutinized for the occurrence of particular sequence signatures that can be associated with certain protein functionalities. Useful sequence signatures not only include short motifs such as protein modification sites or specific binding motifs but also encompass larger protein regions, such as homology domains. There exist a number of fundamentally different bioinformatical data structures, which can be used to store information about sequence signatures, thus making them available for the purpose of protein classification.

Keywords:

  • regular expression;
  • weight matrix;
  • sequence profile;
  • hidden Markov model;
  • homology domains