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Ifptml mapping of drug graphs with protein and chromosome structural networks vs. Pre‐clinical assay information for discovery of antimalarial compounds
ArticleAbstract: The parasite species of genus Plasmodium causes Malaria, which remains a major global health problemPalabras claves:Antimalarial compounds, CHEMBL, complex networks, Machine learning, NCBI‐GDV, perturbation theory, Plasmodium proteome, UniProtAutores:Bernabé Ortega-Tenezaca, González‐díaz H., Quevedo‐tumailli V.Fuentes:scopusMachine learning in antibacterial discovery and development: A bibliometric and network analysis of research hotspots and trends
ArticleAbstract: Machine learning (ML) methods are used in cheminformatics processes to predict the activity of an unPalabras claves:Antibacterial agents, Antibiotic Resistance, Bibliometric Analysis, Computer model in drug design, Machine learning, Network AnalysisAutores:González‐díaz H., Karel Diéguez-SantanaFuentes:googlescopusPredicting multiple drugs side effects with a general drug-target interaction thermodynamic Markov model
ArticleAbstract: Most of present molecular descriptors just consider the molecular structure. In the present articlePalabras claves:Drugs side effects, Markov Model, ThermodynamicsAutores:González‐díaz H., Maykel Cruz-Monteagudo, Molina R., Tenorio E., Uriarte E.Fuentes:scopusPrediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2-Acylpyrrole Derivatives
ArticleAbstract: In this work, the SOFT.PTML tool has been used to pre-process a ChEMBL dataset of pre-clinical assayPalabras claves:Autores:Arrasate S., Barbolla I., Bernabé Ortega-Tenezaca, Dea-Ayuela M.A., Fundora-Ortiz B., González‐díaz H., Lete E., Santiago C., Sotomayor N.Fuentes:scopusMultioutput Perturbation-Theory Machine Learning (PTML) Model of ChEMBL Data for Antiretroviral Compounds
ArticleAbstract: Retroviral infections, such as HIV, are, until now, diseases with no cure. Medicine and pharmaceuticPalabras claves:antiretroviral compounds, BIG DATA, CHEMBL, Machine learning, perturbation theoryAutores:Eduardo Tejera, Emilia Vásquez-Domínguez, González‐díaz H., Vinicio Danilo Armijos-JaramilloFuentes:googlescopusNew 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:scopusSimple stochastic fingerprints towards mathematical modeling in biology and medicine 2. Unifying Markov model for drugs side effects
ArticleAbstract: Most of present mathematical models for biological activity consider just the molecular structure. IPalabras claves:Back-projection analysis, Drugs side effects, linear discriminant analysis, Markov ModelAutores:González‐díaz H., Maykel Cruz-Monteagudo, Uriarte E.Fuentes:scopusUnified drug-target interaction thermodynamic Markov model using stochastic entropies to predict multiple drugs side effects
ArticleAbstract: Most of present molecular descriptors consider just the molecular structure. In the present articlePalabras claves:ADL, Drugs side effects, Markov Model, QSAR, QSTR, thermodynamicAutores:González‐díaz H., Maykel Cruz-MonteagudoFuentes:scopusTrends in Nanoparticles for Leishmania Treatment: A Bibliometric and Network Analysis
ReviewAbstract: Leishmaniasis is a neglected tropical illness with a wide variety of clinical signs ranging from visPalabras claves:Antiprotozoal agents, Bibliometric Analysis, Leishmaniasis treatment, Nanomedicine, Network Analysis, parasite diseasesAutores:Eberto Gutiérrez Morales, Gabriel Mazón-Ortiz, Galo Leonardo Cerda Mejia, González‐díaz H., Karel Diéguez-Santana, Ruso J.M.Fuentes:googleorcidscopus