Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Using a State-Space Model and Location Analysis to Infer Time-Delayed Regulatory Networks | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2009 Article ID 484601 14 pages doi 2009 484601 Research Article Using a State-Space Model and Location Analysis to Infer Time-Delayed Regulatory Networks Chushin Koh 1 Fang-Xiang Wu 2 3 Gopalan Selvaraj 4 and Anthony J. Kusalik1 3 department of Computer Science University of Saskatchewan Saskatoon SK Canada S7N 5C9 department of Mechanical Engineering University of Saskatchewan Saskatoon SK Canada S7N 5A9 division of Biomedical Engineering University of Saskatchewan Saskatoon SK Canada S7N 5A9 4Plant Biotechnology Institute National Research Council of Canada Saskatoon SK Canada S7N 0W9 Correspondence should be addressed to Anthony J. Kusalik kusalik@ Received 31 January 2009 Revised 4 May 2009 Accepted 15 July 2009 Recommended by Seungchan Kim Computational gene regulation models provide a means for scientists to draw biological inferences from time-course gene expression data. Based on the state-space approach we developed a new modeling tool for inferring gene regulatory networks called time-delayed Gene Regulatory Networks tdGRNs . tdGRN takes time-delayed regulatory relationships into consideration when developing the model. In addition a priori biological knowledge from genome-wide location analysis is incorporated into the structure of the gene regulatory network. tdGRN is evaluated on both an artificial dataset and a published gene expression data set. It not only determines regulatory relationships that are known to exist but also uncovers potential new ones. The results indicate that the proposed tool is effective in inferring gene regulatory relationships with time delay. tdGRN is complementary to existing methods for inferring gene regulatory networks. The novel part of the proposed tool is that it is able to infer time-delayed regulatory relationships. Copyright 2009 Chushin Koh et al. This is an open access article distributed under the .