Year: 2020
Type: article
Abstract: Cells estimate concentrations of chemical ligands in their environment using a limited set of receptors. Recent work has shown that the temporal sequence of binding and unbinding events on just a single receptor can be used to estimate the concentrations of multiple ligands. Here, for a network of many ligands and many receptors, we show that such temporal sequences can be used to estimate the concentration of a few times as many ligand species as there are receptors. Crucially, we show that the spectrum of the inverse covariance matrix of these estimates has several universal properties, which we trace to properties of Vandermonde matrices. We argue that this can be used by cells in realistic biochemical decoding networks.
Source: Physical Review Letters
Authors: Vijay Singh, Ilya Nemenman
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Funders: National Science Foundation, Gordon and Betty Moore Foundation, University of Pennsylvania, National Institutes of Health, National Institute of General Medical Sciences, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, Kavli Institute for Theoretical Physics, University of California, Santa Barbara
Awards: G285290610, G3009324719, G439613525, Neural mechanisms and behavioral consequences of non-Gaussian likelihoods in sensorimotor learning, Spike timing codes for motor control, G5808540823, Collaborative Research: Multicellular Communication in Gradient Sensing, Kavli Institute for Theoretical Physics, KITP Interdisciplinary Biology Initiative
OpenAlex ID: W2950518798