Complementary classification approaches for protein sequences

Jason T.L. Wang, Thomas G. Marr, Dennis Shasha, Bruce A. Shapiro, Gung Wei Chirn, T. Y. Lee

Research output: Contribution to journalArticle

Abstract

We have studied five methods of protein classification and have applied them to the 768 groups of related proteins in the PROSITE catalog. Four of these methods are based on searching a database of blocks, and the other uses the frequently occurring motifs found in the protein families combined with a fingerprint technique. Our experimental results show that the block-based methods perform well when taking into account the probability of amino acids occurring in a block. Furthermore, the dive methods give information that is complementary to each other. Thus, using the five methods together, one can obtain high confidence classifications (if the results agree) or suggest alternative hypotheses (if the results disagree). We also list those proteins whose current families documented in the PROSITE catalog differ from those suggested by our results. There are remarkably few of them, which is a testimony to the quality of PROSITE.

Original languageEnglish (US)
Pages (from-to)381-386
Number of pages6
JournalProtein Engineering
Volume9
Issue number5
StatePublished - May 1 1996

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Keywords

  • Block searching
  • Protein classification
  • Protein database
  • SWISS-PROT
  • Statistical approaches

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology

Cite this

Wang, J. T. L., Marr, T. G., Shasha, D., Shapiro, B. A., Chirn, G. W., & Lee, T. Y. (1996). Complementary classification approaches for protein sequences. Protein Engineering, 9(5), 381-386.