@ARTICLE{ iet:/content/journals/10.1049/iet-syb_20060079, author = {M. Bansal}, author = {D. di Bernardo}, ISSN = {1751-8849}, language = {English}, abstract = {Genes interact with each other in complex networks that enable the processing of information and the metabolism of nutrients inside the cell. A novel inference algorithm based on linear ordinary differential equations is proposed. The algorithm can infer the local network of gene–gene interactions surrounding a gene of interest from time-series gene expression profiles. The performance of the algorithm has been tested on in silico simulated gene expression data and on a nine gene subnetwork part of the DNA-damage response pathway (SOS pathway) in the bacteria Escherichia coli. This approach can infer regulatory interactions even when only a small number of measurements is available.}, title = {Inference of gene networks from temporal gene expression profiles}, journal = {IET Systems Biology}, issue = {5}, volume = {1}, year = {2007}, month = {September}, pages = {306-312(6)}, publisher ={Institution of Engineering and Technology}, copyright = {© The Institution of Engineering and Technology}, url = {https://digital-library.theiet.org/;jsessionid=48h0mh5cveg69.x-iet-live-01content/journals/10.1049/iet-syb_20060079} }