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Meta-QSAR: a large-scale application of meta-learning to drug design and discovery
2017
Machine Learning
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study of meta-learning. This application area is of the highest societal importance, as it is a key step in the development of new medicines. The standard QSAR learning problem is: given a target (usually a protein) and a set of chemical compounds (small molecules) with associated bioactivities (e.g. inhibition of the target), learn a predictive mapping from molecular representation to activity.
doi:10.1007/s10994-017-5685-x
pmid:31997851
pmcid:PMC6956898
fatcat:mjfqx65vi5hb5f4hysbcwicaea