Parallel algorithms for Bayesian networks structure learning with applications to systems biology

Olga Nikolova

doi:10.1109/IPDPS.2011.373

Parallel algorithms for Bayesian networks structure learning with applications to systems biology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Bayesian networks (BN) are probabilistic graphical models which are widely utilized in modeling complex biological interactions in the cell. Learning the structure of a BN is an NP-hard problem and existing exact and heuristic solutions do not scale to large enough domains to allow for meaningful modeling of many biological processes. In this work, we present efficient parallel algorithms which push the scale of both exact and heuristic BN structure learning. We demonstrate the applicability of our methods by implementations on an IBM Blue Gene/L and an AMD Opteron cluster, and discuss their significance for future applications to systems biology.

Original language	English (US)
Title of host publication	2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011
Pages	2045-2048
Number of pages	4
DOIs	https://doi.org/10.1109/IPDPS.2011.373
State	Published - 2011
Externally published	Yes
Event	25th IEEE International Parallel and Distributed Processing Symposium, Workshops and Phd Forum, IPDPSW 2011 - Anchorage, AK, United States Duration: May 16 2011 → May 20 2011

Publication series

Name	IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum

Conference

Conference	25th IEEE International Parallel and Distributed Processing Symposium, Workshops and Phd Forum, IPDPSW 2011
Country/Territory	United States
City	Anchorage, AK
Period	5/16/11 → 5/20/11

Keywords

Bayesian networks
Parallel algorithms
Systems biology

ASJC Scopus subject areas

Computational Theory and Mathematics
Software
Theoretical Computer Science

Access to Document

10.1109/IPDPS.2011.373

Cite this

Nikolova, O. (2011). Parallel algorithms for Bayesian networks structure learning with applications to systems biology. In 2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011 (pp. 2045-2048). Article 6009086 (IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum). https://doi.org/10.1109/IPDPS.2011.373

Parallel algorithms for Bayesian networks structure learning with applications to systems biology. / Nikolova, Olga.
2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011. 2011. p. 2045-2048 6009086 (IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nikolova, O 2011, Parallel algorithms for Bayesian networks structure learning with applications to systems biology. in 2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011., 6009086, IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum, pp. 2045-2048, 25th IEEE International Parallel and Distributed Processing Symposium, Workshops and Phd Forum, IPDPSW 2011, Anchorage, AK, United States, 5/16/11. https://doi.org/10.1109/IPDPS.2011.373

Nikolova O. Parallel algorithms for Bayesian networks structure learning with applications to systems biology. In 2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011. 2011. p. 2045-2048. 6009086. (IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum). doi: 10.1109/IPDPS.2011.373

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Parallel algorithms for Bayesian networks structure learning with applications to systems biology

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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