Reverse engineering module networks by PSO-RNN hybrid modeling

Y. Zhang, J. Xuan, B. G. De Los Reyes, R. Clarke, H. W. Ressom

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

1 Scopus citations

Abstract

Finding a transcriptional regulatory network (TRN) is usually an under-determined problem. To address this challenge, we have developed a novel TRN inference method by integrating gene expression data and gene functional category information. The inference is based on module network model. A module is a set of genes with similar expression profiles, and a network represents regulatory relationships between the modules. The proposed method consists of two parts: the module selection part determines the modules with fuzzy c-mean (FCM) clustering by incorporating gene functional category information, and the network inference part uses a hybrid of particle swarm optimization and recurrent neural network (PSO-RNN) methods to infer the underlying network between modules. Our method was tested on real data from two studies: the development of rat central nervous system and the yeast cell cycle process. The results were validated with comparison to various literature sources and gene ontology biological process information.

Original languageEnglish (US)
Title of host publicationProceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
Pages401-407
Number of pages7
StatePublished - 2008
Externally publishedYes
Event2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008 - Las Vegas, NV, United States
Duration: Jul 14 2008Jul 17 2008

Publication series

NameProceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008

Other

Other2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008
CountryUnited States
CityLas Vegas, NV
Period7/14/087/17/08

Keywords

  • Module network
  • Recurrent neural network
  • Swarm intelligence
  • Transcriptional regulatory network

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  • Cite this

    Zhang, Y., Xuan, J., De Los Reyes, B. G., Clarke, R., & Ressom, H. W. (2008). Reverse engineering module networks by PSO-RNN hybrid modeling. In Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008 (pp. 401-407). (Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008).