Diverse mutant selection windows shape spatial heterogeneity in evolving populations.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
06 Sep 2023
Historique:
pubmed: 21 9 2023
medline: 21 9 2023
entrez: 21 9 2023
Statut: epublish

Résumé

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with

Identifiants

pubmed: 37732215
doi: 10.1101/2023.03.09.531899
pmc: PMC10508720
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : NCI NIH HHS
ID : R37 CA244613
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007250
Pays : United States

Auteurs

Eshan S King (ES)

Systems Biology and Bioinformatics Program, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.

Beck Pierce (B)

Department of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University, Cleveland, OH.

Michael Hinczewski (M)

Department of Physics, Case Western Reserve University, Cleveland, OH, USA.

Jacob G Scott (JG)

Systems Biology and Bioinformatics Program, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Department of Physics, Case Western Reserve University, Cleveland, OH, USA.
Department of Translational Hematology and Oncology Research and Radiation Oncology, Cleveland Clinic, Cleveland, OH, USA.

Classifications MeSH