A set-theoretic approach to database searching and clustering

Bioinformatics. 1998 Jun;14(5):430-8. doi: 10.1093/bioinformatics/14.5.430.

Abstract

Motivation: In this paper, we introduce an iterative method of database searching and apply it to design a database clustering algorithm applicable to an entire protein database. The clustering procedure relies on the quality of the database searching routine and further improves its results based on a set-theoretic analysis of a highly redundant yet efficient to generate cluster system.

Results: Overall, we achieve unambiguous assignment of 80% of SWISS-PROT sequences to non-overlapping sequence clusters in an entirely automatic fashion. Our results are compared to an expert-generated clustering for validation. The database searching method is fast and the clustering technique does not require time-consuming all-against-all comparison. This allows for fast clustering of large amounts of sequences.

Availability: The resulting clustering for the PIR1 (Release 51) and SWISS-PROT (Release 34) databases is available over the Internet from http://www.dkfz-heidelberg.de/tbi/services/modest/b rowsesysters.pl.

Contact: [email protected]; [email protected]

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Cluster Analysis
  • Computational Biology
  • Databases, Factual*
  • Proteins / genetics*
  • Sequence Alignment / methods*
  • Sequence Alignment / statistics & numerical data
  • Software

Substances

  • Proteins