Figure 9.
Using regression to predict gene expression. (A) A trivial example where the relationship between expression level (Egx) and TF binding to promoters (Bgf) is found for a single experiment (x) and a single TF (f). Here, the model learns two parameters: the background expression level for all genes in the experiment (F0x) and the activity of the transcription factor in the given experiment (Ffx). (B) The generalized equation for multiple factors and multiple experiments. (C) Matrix representations of the generalized equation. Baseline expression is the same for all genes and so is represented as a single vector multiplied by a row vector of constants where c = 1/(no. genes).