Gaussian Processes and Gene Regulation
Gaussian Processes (Rasmussen and Williams, 2005) can provide a convenient framework for the analysis of gene regulation as shown in two recent papers (Lawrence et al., 2007; Gao et al., 2008). In these two papers, the expression levels of a set of genes were known and they were governed by a common regulatory factor (TF). The unobserved concentration of TF was described by a Gaussian Process. This approach has several advantages and should be explored to the full. Relative to the papers above three useful generalisation immediately springs to mind: Firstly, Multiple TFs. Secondly, Network Models of GR in a single organism, that will allow the TFs to be products of the genes whose expression levels are observed. Thirdly, Network Models and Model Organisms will in the simplest case occur, if experiments in for instance human and mouse have been performed on homologous sets of molecules. A model of the evolution of GR would be needed.
Gaussian Processes (Rasmussen and Williams, 2005) can provide a