Statistical methods for the discovery of co-operative transcription factors: The co-bind code revised

Giovanni Lavorgna, Alessandro Marongiu, Simone Melchionna, Paolo Palazzari, Vittorio Rosato, Paolo Verrecchia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Discovering co-operative Transcription Factors (TF's) within the genome is a computationally challenging problem, tackled through Monte Carlo-like analysis by the Co-Bind code, developed at the Department of Genetics of the St. Louis Washington University, Due to its statistical nature, Co-Bind is characterized by very long execution times, order of days on current high-end workstations, and could benefit from parallelization and a wise optimization, performed at both the algorithmic and coding levels. This work presents the results achieved by parallelizing Co-Bind and optimising the parallel code and shows that, on a 16-processor architecture, a speed-up greater than two orders of magnitude is achieved with respect to the serial version released by the code's authors.

Original languageEnglish
Title of host publicationProceedings - 19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005
Volume2005
DOIs
Publication statusPublished - 2005
Event19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005 - Denver, CO, United States
Duration: Apr 4 2005Apr 8 2005

Other

Other19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005
CountryUnited States
CityDenver, CO
Period4/4/054/8/05

ASJC Scopus subject areas

  • Engineering(all)

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    Lavorgna, G., Marongiu, A., Melchionna, S., Palazzari, P., Rosato, V., & Verrecchia, P. (2005). Statistical methods for the discovery of co-operative transcription factors: The co-bind code revised. In Proceedings - 19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005 (Vol. 2005). [1420095] https://doi.org/10.1109/IPDPS.2005.411