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Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications.

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Title: Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications.
Authors: Guerrero RF; Department of Biological Sciences, North Carolina State University, Raleigh, United States., Dorji T; Department of Mathematics and Statistics, University of Vermont, Burlington, United States., Harris RM; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, United States., Shoulders MD; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, United States., Ogbunugafor CB; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, United States.; Department of Ecology and Evolutionary Biology, Yale University, New Haven, United States.; Santa Fe Institute, Santa Fe, United States.; Public Health Modeling Unit, Yale School of Public Health, New Haven, United States.
Source: ELife [Elife] 2024 Jun 04; Vol. 12. Date of Electronic Publication: 2024 Jun 04.
Publication Type: Journal Article
Journal Info: Publisher: eLife Sciences Publications, Ltd Country of Publication: England NLM ID: 101579614 Publication Model: Electronic Cited Medium: Internet ISSN: 2050-084X (Electronic) Linking ISSN: 2050084X NLM ISO Abbreviation: Elife Subsets: MEDLINE
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        Value: 10.7554/eLife.88480
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