Genome wide association analysis of the 16th QTL- MAS Workshop dataset using the Random Forest machine learning approach
Articolo
Data di Pubblicazione:
2014
Citazione:
Genome wide association analysis of the 16th QTL- MAS Workshop dataset using the Random Forest machine learning approach / G. Minozzi, A. Pedretti, S. Biffani, E.L. Nicolazzi, A. Stella. - In: BMC PROCEEDINGS. - ISSN 1753-6561. - 8:suppl. 5(2014 Oct 07), pp. S4.1-S4.6. [10.1186/1753-6561-8-S5-S4]
Abstract:
Genome wide association studies are now widely used in the livestock sector to estimate the association among single nucleotide polymorphisms (SNPs) distributed across the whole genome and one or more trait. As computational power increases, the use of machine learning techniques to analyze large genome wide datasets becomes possible.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Random Forest ; QTL ; Genomica
Elenco autori:
G. Minozzi, A. Pedretti, S. Biffani, E.L. Nicolazzi, A. Stella
Link alla scheda completa: