Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10362/147672
Título: | The Melting Point Profile of Organic Molecules |
Autor: | Carrera, Gonçalo Valente da Silva Marino |
Palavras-chave: | chemoinformatics codification kohonen neural-networks melting points organic molecules qspr random forests |
Data: | Nov-2022 |
Resumo: | 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. |
Descrição: | |
Peer review: | yes |
URI: | http://hdl.handle.net/10362/147672 |
DOI: | https://doi.org/10.1002/adts.202200503 |
ISSN: | 2513-0390 |
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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