In vivo functional phenotypes from a computational epistatic model of evolution

Computational models of evolution are valuable for understanding the dynamics of sequence variation, to infer phylogenetic relationships or potential evolutionary pathways and for biomedical and industrial applications. Despite these benefits, few have validated their propensities to generate output...

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Veröffentlicht in:	Proceedings of the National Academy of Sciences - PNAS 2024-02, Vol.121 (6), p.e2308895121-e2308895121
Hauptverfasser:	Alvarez, Sophia, Nartey, Charisse M, Mercado, Nicholas, de la Paz, Jose Alberto, Huseinbegovic, Tea, Morcos, Faruck
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Amino acid sequence Biomedical materials Catalysis Computer applications Constraint modelling E coli Epistasis Epistasis, Genetic Evolution, Molecular Evolutionary algorithms Fitness Genetic Fitness Industrial applications Mathematical models Models, Genetic Mutation Phenotype Phenotypes Phylogeny Physical Sciences Protein families Proteins Proteins - genetics Reproductive fitness Vaccine development β Lactamase
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