Cargando…
High throughput mathematical modeling and multi-objective evolutionary algorithms for plant tissue culture media formulation: Case study of pear rootstocks
Simplified prediction of the interactions of plant tissue culture media components is of critical importance to efficient development and optimization of new media. We applied two algorithms, gene expression programming (GEP) and M5’ model tree, to predict the effects of media components on in vitro...
Autores principales: | Jamshidi, Saeid, Yadollahi, Abbas, Arab, Mohammad Mehdi, Soltani, Mohammad, Eftekhari, Maliheh, Shiri, Jalal |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7748151/ https://www.ncbi.nlm.nih.gov/pubmed/33338074 http://dx.doi.org/10.1371/journal.pone.0243940 |
Ejemplares similares
-
Combining gene expression programming and genetic algorithm as a powerful hybrid modeling approach for pear rootstocks tissue culture media formulation
por: Jamshidi, Saeid, et al.
Publicado: (2019) -
Predicting In vitro Culture Medium Macro-Nutrients Composition for Pear Rootstocks Using Regression Analysis and Neural Network Models
por: Jamshidi, S., et al.
Publicado: (2016) -
Mathematical Modeling and Optimizing of in Vitro Hormonal Combination for G × N15 Vegetative Rootstock Proliferation Using Artificial Neural Network-Genetic Algorithm (ANN-GA)
por: Arab, Mohammad M., et al.
Publicado: (2017) -
Modeling and Optimizing a New Culture Medium for In Vitro Rooting of G×N15 Prunus Rootstock using Artificial Neural Network-Genetic Algorithm
por: Arab, Mohammad Mehdi, et al.
Publicado: (2018) -
Artificial Neural Network Genetic Algorithm As Powerful Tool to Predict and Optimize In vitro Proliferation Mineral Medium for G × N15 Rootstock
por: Arab, Mohammad M., et al.
Publicado: (2016)