Literature DB >> 34709534

It doesn't always pay to be fit: success landscapes.

Trung V Phan1,2, Gao Wang3, Tuan K Do4, Ioannis G Kevrekidis5, Sarah Amend6, Emma Hammarlund7, Ken Pienta6, Joel Brown8, Liyu Liu3, Robert H Austin9.   

Abstract

Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.
© 2021. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Cancer; Evolution dynamics; Extinction; Fitness; Landscapes; Mutations; Resources

Mesh:

Year:  2021        PMID: 34709534      PMCID: PMC8603993          DOI: 10.1007/s10867-021-09589-2

Source DB:  PubMed          Journal:  J Biol Phys        ISSN: 0092-0606            Impact factor:   1.365


  1 in total

1.  Robots as models of evolving systems.

Authors:  Gao Wang; Trung V Phan; Shengkai Li; Jing Wang; Yan Peng; Guo Chen; Junle Qu; Daniel I Goldman; Simon A Levin; Kenneth Pienta; Sarah Amend; Robert H Austin; Liyu Liu
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-17       Impact factor: 12.779

  1 in total

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