<p>MotifGP: using multi-objective evolutionary computing for mining network expressions in DNA sequences</p>

Manuel Belmadani; Marcel Turcotte

doi:10.7490/f1000research.1113291.1

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Belmadani M and Turcotte M. MotifGP: using multi-objective evolutionary computing for mining network expressions in DNA sequences [version 1; not peer reviewed]. F1000Research 2016, 5:2518 (slides) (https://doi.org/10.7490/f1000research.1113291.1)

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MotifGP: using multi-objective evolutionary computing for mining network expressions in DNA sequences

Manuel Belmadani¹, Marcel Turcotte²

Published 13 Oct 2016 (https://doi.org/10.7490/f1000research.1113291.1)

Author Affiliations

¹ University of British Columbia, Canada
² University of Ottawa, Canada

Copyright © 2016 Belmadani M and Turcotte M. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 13 Oct 2016

MotifGP: using multi-objective evolutionary computing for mining network expressions in DNA sequences
[version 1; not peer reviewed]

Manuel Belmadani¹, Marcel Turcotte²

Author Affiliations

¹ University of British Columbia, Canada
² University of Ottawa, Canada

Presented at

The Annual IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) 2016

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Transcription factor, binding site, DNA, ChIP-seq, motif, genetic programming, evolutionary algorithm, multi-objective, multiobjective, Pareto, DREME, GP, EA, GA, TF, TFBS, transcription, factor

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