Evidence map›Paper›PMID 30819150›Full record

ArticleBMC systems biology2019

Mathematical modeling of movement on fitness landscapes.

Nishant Gerald, Dibyendu Dutta, R G Brajesh, Supreet Saini

Abstract read
In one paragraph

Article in BMC systems biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Nishant GeraldDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400 076, India.
Dibyendu DuttaDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400 076, India.
R G BrajeshDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400 076, India.
Supreet SainiDepartment of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400 076, India. saini@che.iitb.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMovement of populations on fitness landscapes has been a problem of interest for a long time. While the subject has been extensively developed theoretically, reconciliation of the theoretical work with recent experimental data has not yet happened. In this work, we develop a computational framework and study evolution of the simplest transcription network between a single regulator, R and a single target protein, T.

resultsThrough our simulations, we track evolution of this transcription network and comment on its dynamics and statistics of this movement. Significantly, we report that there exists a critical parameter which controls the ability of a network to reach the global fitness peak on the landscape. This parameter is the fraction of all permissible values of a biochemical parameter that can be accessed from its current value via a single mutation.

conclusionsOverall, through this work, we aim to present a general framework for analysis of movement of populations (and particularly regulatory networks) on landscapes.

Indexed as

Evolution, MolecularGenetic FitnessModels, GeneticMovementSelection, GeneticCost-benefit frameworkFitness landscapeGene regulatory networkOptimal parameters

Identifiers

PMID30819150
PMCPMC6394095

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.