Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification
Abstract Chemical data is increasingly openly available in databases such as PubChem, which contains approximately 110 million compound entries as of February 2021. With the availability of data at such scale, the burden has shifted to organisation, analysis and interpretation. Chemical ontologies p...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2021-03-01
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Series: | Journal of Cheminformatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13321-021-00500-8 |