| Abstract | Many fundamental questions in biology boil down to the relationship between genotype and phenotype. We are working towards a computational model of this relationship, starting with an arbitrary cis-regulatory genotype, and generating a computational phenotype in terms of transcription factor protein concentrations over time. The ultimate goal is to simulate the evolution of this “toy” gene regulatory network. As a component of this larger goal, our model mechanistically simulates transcriptional regulation through interacting transcription factors (TFs) that bind and unbind to available portions of DNA. We must track TF binding configurations for all nucleosome-free regions. This requires the storage of a huge number of potential configurations. This project presents a statistical approach, using a Boltzmann Chain, combined with a thermodynamic framework and dynamic programming to overcome this challenge. |
|---|
