Konwersatorium im. Leopolda Infelda

Many of the biological networks inside cells can be thought of as transmitting information from the inputs (e.g., the concentrations of transcription factors or other signaling molecules) to their outputs (e.g., the expression levels of various genes). Given the molecular limits (small concentrations, intrinsic randomness), not all networks perform equally well, and maximizing information transmission provides a optimization principle from which we might hope to derive the properties of real regulatory networks. Inspired by the precision of transmission of positional information in the early development of the fly embryo, I will discuss the properties of specific small networks that can optimally transmit information. Concretely, I will show how the form of molecular noise drives predictions not just of the qualitative network topology but also how the quantitative parameters for the input/output relations at the nodes of the network depend on the molecular regulator elements. I will then show how we can consider time dependent information transmission.