Continuous abiotic stresses (such as extreme temperatures, high winds and edaphic conditions) can have adverse effects on plant life. This can become a major constraint in crop production. In order to alleviate the problems, it is important to understand the cold stress mechanisms at the molecular and cellular levels, regarding the signaling pathways from cold perception to activation of gene expression. My mentor, Dr. Joan Chen, and her lab, together with other labs, have collected a large amount of DNA microarray data involving plants undergoing cold stresses. I took a system biology approach, aiming to build the gene regulatory network using the cold stress microarray data that have been obtained, to gain a better understanding of plant responses to cold stress at the molecular level. The results generated from this approach will be utilized to generate hypothesis which can be tested by other experimental approaches.

The Dynamic Bayesian Network (DBN) method was chosen to build the transcription regulatory network. This work will show an implementation of Dynamic Bayesian Network (DBN) method and use of the R package, GeneNet, to build a gene regulatory network, which can be easily interpreted by bench scientists.