Vote for your favorite mineral in #MinCup25! - Pectolite vs. Haüyne
It's a pair of striking blue beauties as #pectolite the uncrushable faces off against #hauyne, the phoenix from volcanic ashes!
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Cuesta, Sebastián A., Moreno, Martín, López, Romina A., Mora, José R., Paz, José Luis, Márquez, Edgar A. (2023) ElectroPredictor: An Application to Predict Mayr’s Electrophilicity E through Implementation of an Ensemble Model Based on Machine Learning Algorithms. Journal of Chemical Information and Modeling, 63 (2) 507-521 doi:10.1021/acs.jcim.2c01367

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleElectroPredictor: An Application to Predict Mayr’s Electrophilicity E through Implementation of an Ensemble Model Based on Machine Learning Algorithms
JournalJournal of Chemical Information and Modeling
AuthorsCuesta, Sebastián A.Author
Moreno, MartínAuthor
López, Romina A.Author
Mora, José R.Author
Paz, José LuisAuthor
Márquez, Edgar A.Author
Year2023 (January 23)Volume63
Issue2
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jcim.2c01367Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15679545Long-form Identifiermindat:1:5:15679545:8
GUID0
Full ReferenceCuesta, Sebastián A., Moreno, Martín, López, Romina A., Mora, José R., Paz, José Luis, Márquez, Edgar A. (2023) ElectroPredictor: An Application to Predict Mayr’s Electrophilicity E through Implementation of an Ensemble Model Based on Machine Learning Algorithms. Journal of Chemical Information and Modeling, 63 (2) 507-521 doi:10.1021/acs.jcim.2c01367
Plain TextCuesta, Sebastián A., Moreno, Martín, López, Romina A., Mora, José R., Paz, José Luis, Márquez, Edgar A. (2023) ElectroPredictor: An Application to Predict Mayr’s Electrophilicity E through Implementation of an Ensemble Model Based on Machine Learning Algorithms. Journal of Chemical Information and Modeling, 63 (2) 507-521 doi:10.1021/acs.jcim.2c01367
In(2023, January) Journal of Chemical Information and Modeling Vol. 63 (2) American Chemical Society (ACS)

See Also

These are possibly similar items as determined by title/reference text matching only.

Cabrera, Nicolás, Cuesta, Sebastián A., Mora, José R., Paz, José Luis, Márquez, Edgar A., Espinoza-Montero, Patricio J., Marrero-Ponce, Yovani, Pérez, Noel, Contreras-Torres, Ernesto (2022) Searching glycolate oxidase inhibitors based on QSAR, molecular docking, and molecular dynamic simulation approaches. Scientific Reports, 12 (1) doi:10.1038/s41598-022-24196-4
Cuesta, Sebastián A, Márquez, Edgar A., Loroño, Marcos A., Paz, J.L., Mora, José R. (2021) Theoretical study on the flash vacuum gas-phase pyrolysis reaction mechanism of 2-(2-benzylidenehydrazinyl)pyridine and analogous. Computational and Theoretical Chemistry, 1202. 113297pp. doi:10.1016/j.comptc.2021.113297
De La Torre, Sandra, Cuesta, Sebastián A., Calle, Luis, Mora, José R., Paz, Jose L., Espinoza-Montero, Patricio J., Flores-Sumoza, Máryury, Márquez, Edgar A. (2024) Computational approaches for lead compound discovery in dipeptidyl peptidase-4 inhibition using machine learning and molecular dynamics techniques. Computational Biology and Chemistry, 112. 108145 doi:10.1016/j.compbiolchem.2024.108145
Bernal, Anthony, Márquez, Edgar A., Flores-Sumoza, Máryury, Cuesta, Sebastián A., Mora, José Ramón, Paz, José L., Mendoza-Mendoza, Adel, Rodríguez-Macías, Juan, Salazar, Franklin, Insuasty, Daniel, et al. (2024) Molecular Modeling of Vasodilatory Activity: Unveiling Novel Candidates Through Density Functional Theory, QSAR, and Molecular Dynamics. International Journal of Molecular Sciences, 25 (23). doi:10.3390/ijms252312649
Ferraz-Caetano, José, Teixeira, Filipe, Cordeiro, M. Natália D. S. (2024) Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy. Journal of Chemical Information and Modeling, 64 (7) 2250-2262 doi:10.1021/acs.jcim.3c00544
Liu, Yufeng, Li, Zhenyu (2023) Predict Ionization Energy of Molecules Using Conventional and Graph-Based Machine Learning Models. Journal of Chemical Information and Modeling, 63 (3) 806-814 doi:10.1021/acs.jcim.2c01321
Aguilera-Venegas, Gabriel, López-Molina, Amador, Rojo-Martínez, Gemma, Galán-García, José Luis (2023) Comparing and tuning machine learning algorithms to predict type 2 diabetes mellitus. Journal of Computational and Applied Mathematics, 427. 115115 doi:10.1016/j.cam.2023.115115
de Azevedo, Luis Cesar, Prati, Ronaldo C. (2023) Effect of Flattened Structures of Molecules and Materials on Machine Learning Model Training. Journal of Chemical Information and Modeling, 63 (17) 5446-5456 doi:10.1021/acs.jcim.3c00242
Mendoza, Ivan, Luis Paz, José, González-Paz, Lenin A., Márquez, Edgar A., Vera-Villalobos, Joan, Mora, José R., Alvarado, Ysaias J., Cordova-Sintjago, Tania, Loroño G., Marcos A. (2022) Reaction mechanism of the gas-phase pyrolysis of N – Acetylthiourea and N, N’–diacetylthiourea: A theoretical study based in density functional theory. Computational and Theoretical Chemistry, 1212. 113702 doi:10.1016/j.comptc.2022.113702
Kelleci̇ Çeli̇k, Feyza, Karaduman, Gül (2023) Machine Learning-Based Prediction of Drug-Induced Hepatotoxicity: An OvA-QSTR Approach. Journal of Chemical Information and Modeling, 63 (15) 4602-4614 doi:10.1021/acs.jcim.3c00687
López-López, Edgar, Bajorath, Jürgen, Medina-Franco, José L. (2021) Informatics for Chemistry, Biology, and Biomedical Sciences. Journal of Chemical Information and Modeling, 61 (1) 26-35 doi:10.1021/acs.jcim.0c01301
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 17, 2025 17:15:44
Go to top of page