Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10362/147672
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Campo DC | Valor | Idioma |
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dc.contributor.author | Carrera, Gonçalo Valente da Silva Marino | - |
dc.date.accessioned | 2023-01-16T22:14:42Z | - |
dc.date.available | 2023-12-01T01:31:41Z | - |
dc.date.issued | 2022-11 | - |
dc.identifier.issn | 2513-0390 | - |
dc.identifier.other | PURE: 47181119 | - |
dc.identifier.other | PURE UUID: 4f4a4c43-bef5-41f9-ad97-41122c7fbcf3 | - |
dc.identifier.other | Scopus: 85139858922 | - |
dc.identifier.other | WOS: 000868840300001 | - |
dc.identifier.uri | http://hdl.handle.net/10362/147672 | - |
dc.description | - | |
dc.description.abstract | The combination of the generical molecular maps of atom-level properties (MOLMAPs) encoding approach and the Random Forest algorithm (RF) is applied in order to model, predict, and interpret the structural motifs responsible for a certain organic molecule's melting point (mp) profile. A high-quality database is used for model build-up and evaluation of predictive ability. The obtained results for the complete independent test set (R2 = 0.811, MAE = 31.99 K, RMS = 43.98 K) are comparable or better than reference works. The form of codification represents implicitly the structure of a given molecule and highlights the interactions responsible for a certain melting point profile. This generical encoding approach groups different structural motifs based on its calculated atomic-based properties leading to good predictive ability for structurally different chemical systems not contained in the training set. | en |
dc.language.iso | eng | - |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50006%2F2020/PT | - |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50006%2F2020/PT | - |
dc.rights | openAccess | pt_PT |
dc.subject | chemoinformatics | - |
dc.subject | codification | - |
dc.subject | kohonen neural-networks | - |
dc.subject | melting points | - |
dc.subject | organic molecules | - |
dc.subject | qspr | - |
dc.subject | random forests | - |
dc.title | The Melting Point Profile of Organic Molecules | - |
dc.type | article | - |
degois.publication.issue | 11 | - |
degois.publication.title | Advanced Theory and Simulations | - |
degois.publication.volume | 5 | - |
dc.peerreviewed | yes | - |
dc.identifier.doi | https://doi.org/10.1002/adts.202200503 | - |
dc.description.version | authorsversion | - |
dc.description.version | published | - |
dc.title.subtitle | A Chemoinformatic Approach | - |
dc.contributor.institution | DQ - Departamento de Química | - |
dc.contributor.institution | LAQV@REQUIMTE | - |
Aparece nas colecções: | Home collection (FCT) |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2_advtheorysimul_Accepted_Version2022.pdf | 1,13 MB | Adobe PDF | Ver/Abrir |
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