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Developing Systems Bioinformatics to Modeling and Deciphering Plant Transcriptional Regulatory Networks

The Zhao Bioinformatics Lab at the Samuel Roberts Noble Foundation is awarded a grant (NSF award #0960897) to investigate how genome scale transcriptional regulatory networks control gene expression. The work was initially supported by the Oklahoma Center for the Advancement of Science & Technology (OCAST Project PSB09-32) and the Samuel Roberts Noble Foundation. The project is designed to address diversity and complexity of gene regulation in plant systems and key regulatory elements, including transcription factors, microRNAs (miRNAs), trans-acting small interfering RNAs (ta-siRNAs), and emergent regulatory elements. The specific objectives of the project are

• to develop graphical models to model and simulate plant transcriptional regulatory networks;
• to develop novel computational algorithms to infer large-scale gene regulatory networks (GRNs) from high throughput functional genomics data in model plants;
• to construct Arabidopsis Gene Regulation Networks (AGRNs) focusing on hormone-related regulatory networks;
• to construct Legume Gene Regulatory Networks (LGRNs) involved in regulation of nodulation in three model legumes: Medicago truncatula, Lotus japonicus, and Glycine max;
• to develop integrated web systems to host GRNs along with supportive genome-scale data, and the network discovery, search and curation tools.

Our central methods involve (1) modeling and simulation of genome-scale associations, including causal relationships, among key regulatory elements such as genes, functional non-coding RNAs, proteins, metabolites, signaling components and other emergent properties using graphical models; (2) novel informatics for discovering and inferring large-scale gene regulatory networks from high throughput Microarray based and RNA-Seq based gene expression data, and (3) system and data integration to elucidate networks.