Modeling transcriptional regulation in chondrogenesis using particle swarm optimization

Yunlong Liu, Hiroki Yokota

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

5 Scopus citations

Abstract

Chondrogenesis is a complex developmental process Involving many transcription factors. Using mRNA expression data and regulatory DNA sequences, we formulated a quantitative model to predict a set of transcription-factor binding motifs (TFBMs) as a combinatorial problem. To solve such a problem, an efficient computational algorithm should be employed. In the current study, particle swarm optimization was applied. Swarm intelligence is an artificial intelligence approach that mimics a behavior of swarm-forming agents. Such systems are made up with a population of individuals that interact locally and globally. Here, a group of TFBMs was predicted using 200 artificial bees and the results were compared to biologically known binding motifs.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05
StatePublished - Dec 1 2005
Externally publishedYes
Event2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05 - La Jolla, CA, United States
Duration: Nov 14 2005Nov 15 2005

Publication series

NameProceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05
Volume2005

Other

Other2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05
CountryUnited States
CityLa Jolla, CA
Period11/14/0511/15/05

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Liu, Y., & Yokota, H. (2005). Modeling transcriptional regulation in chondrogenesis using particle swarm optimization. In Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05 [1594934] (Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05; Vol. 2005).