On signalling and estimation limits for molecular birth-processes

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Title: On signalling and estimation limits for molecular birth-processes
Authors: Parag, KV
Item Type: Journal Article
Abstract: Understanding and uncovering the mechanisms or motifs that molecular networks employ to regulate noise is a key problem in cell biology. As it is often difficult to obtain direct and detailed insight into these mechanisms, many studies instead focus on assessing the best precision attainable on the signalling pathways that compose these networks. Molecules signal one another over such pathways to solve noise regulating estimation and control problems. Quantifying the maximum precision of these solutions delimits what is achievable and allows hypotheses about underlying motifs to be tested without requiring detailed biological knowledge. The pathway capacity, which defines the maximum rate of transmitting information along it, is a widely used proxy for precision. Here it is shown, for estimation problems involving elementary yet biologically relevant birth-process networks, that capacity can be surprisingly misleading. A time-optimal signalling motif, called birth-following, is derived and proven to better the precision expected from the capacity, provided the maximum signalling rate constraint is large and the mean one above a certain threshold. When the maximum constraint is relaxed, perfect estimation is predicted by the capacity. However, the true achievable precision is found highly variable and sensitive to the mean constraint. Since the same capacity can map to different combinations of rate constraints, it can only equivocally measure precision. Deciphering the rate constraints on a signalling pathway may therefore be more important than computing its capacity.
Issue Date: 7-Nov-2019
Date of Acceptance: 9-Jul-2019
URI: http://hdl.handle.net/10044/1/71867
DOI: 10.1016/j.jtbi.2019.07.007
ISSN: 0022-5193
Publisher: Elsevier
Start Page: 262
End Page: 273
Journal / Book Title: Journal of Theoretical Biology
Volume: 480
Copyright Statement: © 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/.
Keywords: Science & Technology
Life Sciences & Biomedicine
Mathematical & Computational Biology
Life Sciences & Biomedicine - Other Topics
Molecular estimation
Information theoretic bounds
Queueing theory
Cellular signalling
Intrinsic noise
Cellular signalling
Information theoretic bounds
Intrinsic noise
Molecular estimation
Queueing theory
Evolutionary Biology
01 Mathematical Sciences
06 Biological Sciences
08 Information and Computing Sciences
Publication Status: Published
Embargo Date: 2020-07-09
Online Publication Date: 2019-07-09
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care

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