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Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays.
Li, Fangfei; Tarkington, Jason; Sherlock, Gavin.
Afiliación
  • Li F; Department of Genetics, Stanford University, Stanford, USA.
  • Tarkington J; Department of Genetics, Stanford University, Stanford, USA.
  • Sherlock G; Department of Genetics, Stanford University, Stanford, USA. gsherloc@stanford.edu.
J Mol Evol ; 91(3): 334-344, 2023 06.
Article en En | MEDLINE | ID: mdl-36877292
The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell's ability to reproduce. Here, we describe an improved approach, implemented in Python, for estimating fitness in high throughput via pooled competition assays.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reproducción / Programas Informáticos Idioma: En Revista: J Mol Evol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reproducción / Programas Informáticos Idioma: En Revista: J Mol Evol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania