Year: 2002
Type: preprint
Abstract: Motivated by recent experimental developments in functional genomics, we construct and test a numerical technique for inferring it process pathways, in which one process calls another process, from time series data. We validate using a case in which data are readily available and formulate an extension, appropriate for genetic regulatory networks, which exploits Bayesian inference and in which the present--day undersampling is compensated for by prior understanding of genetic regulation.
Source: arXiv (Cornell University)
Authors: Wiggins, Chris, Nemenman, Ilya
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4394662758