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1دورية أكاديمية
المؤلفون: Juan F. Avellaneda-Tamayo, Ana L. Chávez-Hernández, Diana L. Prado-Romero, José L. Medina-Franco
مصطلحات موضوعية: Biochemistry, Pharmacology, Ecology, Sociology, Science Policy, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, using different sets, several apolar structures, maximum common substructures, marked economic implications, distinctive physicochemical properties, food component structures, large molecular weights, high structural complexity, food components addressed, food chemicals showed, chemical multiverse representation, 3 sup, food chemical compounds, food components, food chemicals, chemical multiverse, food industry, structural features, omics <, chemical space, chemical contents, 500 compounds
الإتاحة: https://doi.org/10.1021/acs.jcim.3c01617.s001Test
https://figshare.com/articles/journal_contribution/Chemical_Multiverse_and_Diversity_of_Food_Chemicals/25224109Test -
2دورية أكاديمية
المؤلفون: Juan F. Avellaneda-Tamayo, Ana L. Chávez-Hernández, Diana L. Prado-Romero, José L. Medina-Franco
مصطلحات موضوعية: Biochemistry, Pharmacology, Ecology, Sociology, Science Policy, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, using different sets, several apolar structures, maximum common substructures, marked economic implications, distinctive physicochemical properties, food component structures, large molecular weights, high structural complexity, food components addressed, food chemicals showed, chemical multiverse representation, 3 sup, food chemical compounds, food components, food chemicals, chemical multiverse, food industry, structural features, omics <, chemical space, chemical contents, 500 compounds
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3دورية أكاديمية
مصطلحات موضوعية: Medicine, Biotechnology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Information Systems not elsewhere classified, autoencoder neural network, forecasting physical properties, 500 compounds represented, chemical substances based, process organic substances, latent space properties, final ae model, latent space, organic compounds, physicochemical properties, 5276 substances, final step, based representation, organic molecules, ae training, ae descriptors, three configurations, smiles strings, smiles representation, regression task, qspr model, predictive ability, potential modeling, potential development
الإتاحة: https://doi.org/10.1021/acs.jcim.3c01548.s001Test
https://figshare.com/articles/journal_contribution/Transformer-Based_Representation_of_Organic_Molecules_for_Potential_Modeling_of_Physicochemical_Properties/24770713Test