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Content Provider | IEEE Xplore Digital Library |
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Author | Chang, D.T.-H. Guan-Yu Shiu You-Jie Sun |
Copyright Year | 2014 |
Description | Author affiliation: Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan (Chang, D.T.-H.; Guan-Yu Shiu; You-Jie Sun) |
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. |
Starting Page | 491 |
Ending Page | 494 |
File Size | 305935 |
Page Count | 4 |
File Format | |
ISBN | 9781479928378 |
DOI | 10.1109/ICCA.2014.6870968 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-06-18 |
Publisher Place | Taiwan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Customer relationship management Databases Equations Genomics Hidden Markov models Standards DNA transcription factor binding site cis-regulatory module |
Content Type | Text |
Resource Type | Article |
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