On Cooperative Quasi-Equilibrium Models of transcriptional Regulation

Mechanistic models for transcriptional regulation are derived using the methods of equilibrium statistical mechanics, to model equilibrating processes that occur at a fast time scale. These processes regulate slower changes in the synthesis and expression of transcription factors that feed back and cooperatively regulate transcription, forming a gene regulation network (GRN). We rederive and extend two previous quasi-equilibrium models of transcriptional regulation, and demonstrate circumstances under which they can be approximated by feed-forward artificial neural network (ANN) models. A single-level mechanistic model can be approximated for each transcription complex by a successfully used phenomenological model of GRNs which is based on single-layer analog-valued ANNs. A two-level hierarchical mechanistic model, with separate activation states for modules and for the whole transcription complex, can be approximated for each transcription complex by a two-layer feed-forward ANN in s...

• Type: Journal
• Year: 2007
• Where: JBCB
• Authors: Eric Mjolsness
• Keywords: JBCB 2007, Mechanistic Models, Single-level Mechanistic Model, Transcriptional Regulation