Predicting cis-regulatory modules by method integration

Tien-Hao Chang, Guan Yu Shiu, You Jie Sun

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

Abstract

Various cis-regulatory module (CRM) predictors have been proposed in the last decade. Several well-established CRM predictors adopted different categories of prediction strategies, including window clustering, probabilistic modeling and phylogenetic footprinting. Appropriate integration of them has a potential to achieve high quality CRM prediction. This study analyzed four existing CRM predictors (ClusterBuster, MSCAN, CisModule and MultiModule) to seek a predictor combination that delivers a higher accuracy than individual CRM predictors. 465 CRMs across 140 Drosophila melanogaster genes from the REDfly database were used to evaluate the integrated CRM predictor proposed in this study. The results show that four predictor combinations achieved superior performance than the best individual CRM predictor.

Original languageEnglish
Title of host publication11th IEEE International Conference on Control and Automation, IEEE ICCA 2014
PublisherIEEE Computer Society
Pages491-494
Number of pages4
ISBN (Print)9781479928378
DOIs
Publication statusPublished - 2014 Jan 1
Event11th IEEE International Conference on Control and Automation, IEEE ICCA 2014 - Taichung, Taiwan
Duration: 2014 Jun 182014 Jun 20

Publication series

NameIEEE International Conference on Control and Automation, ICCA
ISSN (Print)1948-3449
ISSN (Electronic)1948-3457

Other

Other11th IEEE International Conference on Control and Automation, IEEE ICCA 2014
CountryTaiwan
CityTaichung
Period14-06-1814-06-20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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  • Cite this

    Chang, T-H., Shiu, G. Y., & Sun, Y. J. (2014). Predicting cis-regulatory modules by method integration. In 11th IEEE International Conference on Control and Automation, IEEE ICCA 2014 (pp. 491-494). [6870968] (IEEE International Conference on Control and Automation, ICCA). IEEE Computer Society. https://doi.org/10.1109/ICCA.2014.6870968