Speaker
Description
Discrete models are a natural framework for biological systems whose regulation is governed by switch-like interactions. In this talk, we will present a reverse-engineering approach to Boolean modeling of mammalian cell division through the regulation of the transcription factor E2F. Starting from partial biological knowledge about the roles of CycB, Rb, p27, and CycA, we will show how a prescribed canalizing-layer structure can be used to recover a family of nested canalizing Boolean functions consistent with the known regulatory logic. This framework makes it possible to encode dominant regulatory effects, distinguish variables acting at different hierarchical levels, and systematically infer admissible update rules from incomplete mechanistic information.
