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New experimental and computational tools for drug discovery: Medicinal chemistry, molecular docking, and machine learning - Part-VI
OtherAbstract:Palabras claves:Autores:González‐díaz H., Maykel Cruz-MonteagudoFuentes:scopusPbkp_redicting metabolic reaction networks with Perturbation-Theory Machine Learning (PTML) models
ArticleAbstract: Background: Checking the connectivity (structure) of complex Metabolic Reaction Networks (MRNs) modePalabras claves:Combinatorial perturbation theory models, complex networks, Linear invariants, Machine learning, Markov chains, Metabolic pathwaysAutores:Gerardo M. Casañola-Martin, González‐díaz H., Green J.R., Karel Diéguez-Santana, Rasulev B.Fuentes:googlescopusPtml multi-label algorithms: Models, software, and applications
ReviewAbstract: By combining Machine Learning (ML) methods with Perturbation Theory (PT), it is possi-ble to developPalabras claves:Cheminformatics, Drug Discovery, Large data sets, Machine learning, Multi-target models, perturbation theory, PTMLAutores:Arrasate S., Bediaga H., Bernabé Ortega-Tenezaca, Collados J., González‐díaz H., Madariaga G., Munteanu C.R., Natalia Dias Soeiro Cordeiro M., Quevedo‐tumailli V.Fuentes:scopus