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1LocusSim a mobile-friendly simulator for teaching population genetics
Identificadores del recurso
Bioinformatics Advances, 3(1): vbad087 (2023)
26350041
http://hdl.handle.net/11093/5253
10.1093/bioadv/vbad087
https://academic.oup.com/bioinformaticsadvances/article/doi/10.1093/bioadv/vbad087/7219713
Procedencia
(Investigo)

Ficha

Título:
1LocusSim a mobile-friendly simulator for teaching population genetics
Tema:
2409.03 Genética de Poblaciones
Descrición:
MOTIVATION: Biology students often struggle with the fundamental concepts of evolutionary genetics, including genetic drift, mutation and selection. To address this problem, 1LocusSim was developed to simulate the interaction of different factors, such as population size, mutation, selection and dominance, to study their effect on allelic frequency during evolution. With 1LocusSim, students can compare theoretical results with simulation outputs and solve and analyze different problems of population genetics. The 1LocusSim web has a responsive design which means that it has been specifically designed to be used on smartphones. RESULTS: To demonstrate its use, I review the classical overdominance model of population genetics and highlight a characteristic that is often not explicitly stated. Specifically, it is emphasized that the equilibrium of the model does not depend on the homozygous selection coefficients but rather on the ratio of the selection coefficients. This is already clear from the classical formula but maybe not so much for students. Also it implies that the equilibrium can be expressed solely in terms of the dominance coefficient h. To verify this theoretical prediction, I utilize the simulator and calculate the equilibrium for the well-known case of sickle cell anemia. By utilizing this tool, students can learn at their own pace and convenience, anywhere and anytime. AVAILABILITY IMPLEMENTATION: 1LocusSim if freely available at https://1LocusSim-biosdev.pythonanywhere.com/. Website implemented under the Bottle micro web-framework for Python, with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online.
Xunta de Galicia | Ref. ED431C 2020/05
Universidade de Vigo/CISUG
Idioma:
English
Autor/Productor:
Carvajal Rodríguez, Antonio
Editor:
Bioinformatics Advances
Bioquímica, xenética e inmunoloxía
Xenética de Poboacións e Citoxenética
Dereitos:
Atribución 4.0 Internacional
https://creativecommons.org/licenses/by/4.0/deed.es
openAccess
Data:
2023-10-13T12:06:03Z
2023-07-05
2023-10-13T10:45:37Z
Tipo de recurso:
article

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