2000 character limit reached
Evolving Boolean Regulatory Networks with Variable Gene Expression Times
Published 2 Mar 2016 in q-bio.BM, cs.NE, and q-bio.MN | (1603.01185v2)
Abstract: The time taken for gene expression varies not least because proteins vary in length considerably. This paper uses an abstract, tuneable Boolean regulatory network model to explore gene expression time variation. In particular, it is shown how non-uniform expression times can emerge under certain conditions through simulated evolution. That is, gene expression time variance appears beneficial in the shaping of the dynamical behaviour of the regulatory network without explicit consideration of protein function.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.