Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sofia Ramos-Pulido"'
Autor:
Osval A. Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, Bernabe Cano-Paez, Gloria Isabel Huerta-Prado, Brandon Alejandro Mosqueda-González, Sofia Ramos-Pulido, Guillermo Gerard, Khalid Alnowibet, Roberto Fritsche-Neto, Abelardo Montesinos-López, José Crossa
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionBecause Genomic selection (GS) is a predictive methodology, it needs to guarantee high-prediction accuracies for practical implementations. However, since many factors affect the prediction performance of this methodology, its practical i
Externí odkaz:
https://doaj.org/article/bc352c418ea44b3aa88d1cf294b125fa
Autor:
Osval A. Montesinos-López, Mario Alberto Solis-Camacho, Leonardo Crespo-Herrera, Carolina Saint Pierre, Gloria Isabel Huerta Prado, Sofia Ramos-Pulido, Khalid Al-Nowibet, Roberto Fritsche-Neto, Guillermo Gerard, Abelardo Montesinos-López, José Crossa
Publikováno v:
Genes, Vol 15, Iss 3, p 286 (2024)
Genomic selection (GS) is revolutionizing plant breeding. However, its practical implementation is still challenging, since there are many factors that affect its accuracy. For this reason, this research explores data augmentation with the goal of im
Externí odkaz:
https://doaj.org/article/2274da15ecfa4c92bbea7ad8059f1033
Autor:
Osval A. Montesinos-López, Sofia Ramos-Pulido, Carlos Moisés Hernández-Suárez, Brandon Alejandro Mosqueda González, Felícitas Alejandra Valladares-Anguiano, Paolo Vitale, Abelardo Montesinos-López, José Crossa
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
IntroductionGenomic selection (GS) has gained global importance due to its potential to accelerate genetic progress and improve the efficiency of breeding programs.Objectives of the researchIn this research we proposed a method to improve the predict
Externí odkaz:
https://doaj.org/article/73541120d2894d3b9cbd8a631542b77a
Publikováno v:
Informatics, Vol 11, Iss 1, p 6 (2024)
Current research on the career satisfaction of graduates limits educational institutions in devising methods to attain high career satisfaction. Thus, this study aims to use data science models to understand and predict career satisfaction based on i
Externí odkaz:
https://doaj.org/article/6826ac74c4244f2291768cac9a44fe76
Publikováno v:
Informatics, Vol 10, Iss 1, p 23 (2023)
This study shows the significant features predicting graduates’ job levels, particularly high-level positions. Moreover, it shows that data science methodologies can accurately predict graduate outcomes. The dataset used to analyze graduate outcome
Externí odkaz:
https://doaj.org/article/7cb770176bdc4ae587ca08d32074340b