Sparse estimation of mutual information landscapes quantifies information transmission through cellular biochemical reaction networks

Published

April 30, 2020

Author(s)

Swarnavo Sarkar, Drew S. Tack, David Ross

Abstract

Measuring information transmission from stimulus to response is useful for evaluating the signaling fidelity of biochemical reaction networks (BRNs) in cells. Quantification of information transmission can reveal the optimal input stimuli environment for a BRN and the rate at which the signaling fidelity decreases for non-optimal input probability distributions. Here we present sparse estimation of mutual information landscapes (SEMIL), a method to quantify information transmission through cellular BRNs using commonly available data for single-cell gene expression output, across a design space of possible input distributions. We validate SEMIL and use it to analyze several engineered cellular sensing systems to demonstrate the impact of reaction pathways and rate constants on mutual information landscapes.

Citation

Communications Biology

Volume

3

Issue

1

Pub Type

Journals

Download Paper

https://doi.org/10.1038/s42003-020-0901-9

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Keywords

mutual information, gene expression, flow cytometry, response function

Citation

Sarkar, S. , Tack, D. and Ross, D. (2020), Sparse estimation of mutual information landscapes quantifies information transmission through cellular biochemical reaction networks, Communications Biology, [online], https://doi.org/10.1038/s42003-020-0901-9 (Accessed November 2, 2025)