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. |
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| 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 |
| Database: | MEDLINE Ultimate |
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