Indexing schemes for similarity search in datasets of short protein fragments

  • Authors:

  • Aleksandar Stojmirović;Vladimir Pestov

  • Affiliations:

  • Department of Mathematics and Statistics, University of Ottawa, 585 King Edward Avenue, Ottawa, Ont., Canada K1N 6N5;Department of Mathematics and Statistics, University of Ottawa, 585 King Edward Avenue, Ottawa, Ont., Canada K1N 6N5

  • Venue:
  • Information Systems
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose a family of very efficient hierarchical indexing schemes for ungapped, score matrix-based similarity search in large datasets of short (4-12 amino acid) protein fragments. This type of similarity search has importance in both providing a building block to more complex algorithms and for possible use in direct biological investigations where datasets are of the order of 60 million objects. Our scheme is based on the internal geometry of the amino acid alphabet and performs exceptionally well, for example outputting 100 nearest neighbours to any possible fragment of length 10 after scanning on average less than 1% of the entire dataset.