Estimating seed sensitivity on homogeneous alignments
Other Computer Science
2011-01-18 v1
Abstract
We address the problem of estimating the sensitivity of seed-based similarity search algorithms. In contrast to approaches based on Markov models [18, 6, 3, 4, 10], we study the estimation based on homogeneous alignments. We describe an algorithm for counting and random generation of those alignments and an algorithm for exact computation of the sensitivity for a broad class of seed strategies. We provide experimental results demonstrating a bias introduced by ignoring the homogeneousness condition.
Keywords
Cite
@article{arxiv.cs/0603106,
title = {Estimating seed sensitivity on homogeneous alignments},
author = {Gregory Kucherov and Laurent Noe and Yann Ponty},
journal= {arXiv preprint arXiv:cs/0603106},
year = {2011}
}