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)

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