Efficient phenotypic sex classification of zebrafish using machine learning methods

Sex determination in zebrafish by manual approaches according to current guidelines relies on human observation. These guidelines for sex recognition have proven to be subjective and highly labor‐intensive. To address this problem, we present a methodology to automatically classify the phenotypic se...

Descripción completa

Detalles Bibliográficos
Autores principales: Hosseini, Shahrbanou, Simianer, Henner, Tetens, Jens, Brenig, Bertram, Herzog, Sebastian, Sharifi, Ahmad Reza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912926/
https://www.ncbi.nlm.nih.gov/pubmed/31871648
http://dx.doi.org/10.1002/ece3.5788

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912926/
https://www.ncbi.nlm.nih.gov/pubmed/31871648
http://dx.doi.org/10.1002/ece3.5788

Ejemplares similares