A random forest model for predicting the crystallisability of organic molecules
Tools
Bhardwaj, Rajni M. and Johnston, Andrea and Johnston, Blair F. and Florence, Alastair J. (2015) A random forest model for predicting the crystallisability of organic molecules. CrystEngComm, 17 (23). pp. 4272-4275. ISSN 1466-8033 (https://doi.org/10.1039/c4ce02403f)
Preview |
Text.
Filename: Bhardwaj_etal_CEC2015_random_forest_model_for_predicting_the_crystallisability_of_organic_molecules.pdf
Accepted Author Manuscript Download (776kB)| Preview |
Abstract
A random forest model has for the first time enabled the prediction of the crystallisability (crystals vs. no crystals) of organic molecules with ∼70% accuracy. The predictive model is based on calculated molecular descriptors and published experimental crystallisation propensities of a library of substituted acylanilides.
ORCID iDs
Bhardwaj, Rajni M., Johnston, Andrea, Johnston, Blair F. ORCID: https://orcid.org/0000-0001-9785-6822 and Florence, Alastair J. ORCID: https://orcid.org/0000-0002-9706-8364;-
-
Item type: Article ID code: 57641 Dates: DateEvent21 June 2015Published16 February 2015Published Online16 February 2015AcceptedSubjects: Medicine > Pharmacy and materia medica Department: University of Strathclyde > University of Strathclyde
Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences
Technology and Innovation Centre > Continuous Manufacturing and Crystallisation (CMAC)Depositing user: Pure Administrator Date deposited: 01 Sep 2016 11:28 Last modified: 28 Nov 2024 01:11 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/57641
CORE (COnnecting REpositories)