2024-03-28T09:20:29Zhttp://buleria.unileon.es/oai/requestoai:buleria.unileon.es:10612/105722020-12-10T08:56:03Zcom_10612_17col_10612_18
Statistical Series: Opportunities and challenges of sperm motility subpopulation analysis
Martínez Pastor, Felipe
Tizado Morales, Emilio Jorge
Garde López-Brea, Julián
Anel Rodríguez, Luis
Paz Cabello, Paulino de
Biologia Celular
Veterinaria
Computer-assisted sperm analysis (CASA) allows assessing the motility of individual spermatozoa, generating huge datasets. These datasets can be analyzed using data mining techniques such as cluster analysis, to group the spermatozoa in subpopulations with biological meaning. This review considers the use of statistical techniques for clustering CASA data, their challenges and possibilities. There are many clustering approaches potentially useful for grouping sperm motility data, but some options may be more appropriate than others. Future development should focus not only in improvements of subpopulation analysis, but also in finding consistent biological meanings for these subpopulations.
2019-04-22T23:23:16Z
2019-04-22T23:23:16Z
2019-04-22T23:23:16Z
2019-04-23
info:eu-repo/semantics/article
Theriogenology, 2011, vol. 75, n. 5
https://www.sciencedirect.com/science/article/pii/S0093691X10006278#!
http://hdl.handle.net/10612/10572
Elsevier