title: Mutual information between input and output trajectories of biochemical networks.
abstract: Biochemical networks can respond to temporal characteristics of time-varying signals. To understand how reliably biochemical networks can transmit information we must consider how an input signal as a function of time--the input trajectory--can be mapped onto an output trajectory. Here we estimate the mutual information between input and output trajectories using a Gaussian model. We study how reliably the chemotaxis network of E. coli can transmit information on the ligand concentration to the flagellar motor, and find the input power spectrum that maximizes the information transmission rate.
authors.affiliation: FOM Institute for Atomic and Molecular Physics, Kruislaan 407, 1098 SJ Amsterdam, The Netherlands.
authors.forename: Filipe
authors.initials: F
authors.lastname: Tostevin
authors.forename: Pieter Rein
authors.initials: PR
authors.lastname: ten Wolde
mesh_terms: D000465:Algorithms; D002633:Chemotaxis; D004926:Escherichia coli / Q000502:physiology*; D005407:Flagella / Q000378:metabolism*; D008024:Ligands; D053858:Metabolic Networks and Pathways; D016011:Normal Distribution; D011485:Protein Binding; D015398:Signal Transduction; D013997:Time Factors; D015533:Transcriptional Activation
chemical_list: D008024:Ligands