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Motif-grasp and motif-ils: two new stochastic local search algorithms for motif finding

Motif-grasp and motif-ils: two new stochastic local search algorithms for motif finding
Motif-grasp and motif-ils: two new stochastic local search algorithms for motif finding
Motif finding in biosequences is a very important and well-studied problem. However, the best algorithms to date either give a poor performance on some problem instances, or are computationally impractical. As it turns out that this problem is computationally hard, in this work, we propose Motif-GRASP, a GRASP algorithm, and Motif-ILS, an ILS algorithm, to solve the motif finding problem. We have tested the two algorithms on data sets generated with the Motif-Generator we have implemented, and found that they both algorithms work pretty well, with a better performance for the GRASP algorithm. Motif-GRASP also works well for the CRP real data set, and both algorithms perform poorly for simulated sets from the Challenge Problem [9]. The results presented in this work are promising, and maybe with more improvement, we can get results comparable with state of the art algorithms for this problem.
Andronescu, Mirela
345bb228-f8cc-4bf9-bebb-00e1fefdff89
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Andronescu, Mirela
345bb228-f8cc-4bf9-bebb-00e1fefdff89
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1

Andronescu, Mirela and Rastegari, Baharak (2003) Motif-grasp and motif-ils: two new stochastic local search algorithms for motif finding. Mini Workshop on Stochastic Search Algorithms, Room 1613, Forest Sciences Centre, University of British Columbia, Vancouver, Canada. 25 Apr 2003. 68 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

Motif finding in biosequences is a very important and well-studied problem. However, the best algorithms to date either give a poor performance on some problem instances, or are computationally impractical. As it turns out that this problem is computationally hard, in this work, we propose Motif-GRASP, a GRASP algorithm, and Motif-ILS, an ILS algorithm, to solve the motif finding problem. We have tested the two algorithms on data sets generated with the Motif-Generator we have implemented, and found that they both algorithms work pretty well, with a better performance for the GRASP algorithm. Motif-GRASP also works well for the CRP real data set, and both algorithms perform poorly for simulated sets from the Challenge Problem [9]. The results presented in this work are promising, and maybe with more improvement, we can get results comparable with state of the art algorithms for this problem.

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More information

Published date: 2003
Venue - Dates: Mini Workshop on Stochastic Search Algorithms, Room 1613, Forest Sciences Centre, University of British Columbia, Vancouver, Canada, 2003-04-25 - 2003-04-25

Identifiers

Local EPrints ID: 426391
URI: http://eprints.soton.ac.uk/id/eprint/426391
PURE UUID: 4543e8c6-eab7-45ff-94b5-456bd9ea9491
ORCID for Baharak Rastegari: ORCID iD orcid.org/0000-0002-0985-573X

Catalogue record

Date deposited: 27 Nov 2018 17:30
Last modified: 10 Nov 2021 03:56

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Contributors

Author: Mirela Andronescu
Author: Baharak Rastegari ORCID iD

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