About: Active learning strategies with COMBINE analysis: new tricks for an old dog

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About: Active learning strategies with COMBINE analysis: new tricks for an old dog Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Active learning strategies with COMBINE analysis: new tricks for an old dog
Creator	Cabrera, Alvaro Fusani, Lucia
Source	Medline; PMC
abstract	The COMBINE method was designed to study congeneric series of compounds including structural information of ligand–protein complexes. Although very successful, the method has not received the same level of attention than other alternatives to study Quantitative Structure Active Relationships (QSAR) mainly because lack of ways to measure the uncertainty of the predictions and the need for large datasets. Active learning, a semi-supervised learning approach that makes use of uncertainty to enhance models’ performance while reducing the size of the training sets, has been used in this work to address both problems. We propose two estimators of uncertainty: the pool of regressors and the distance to the training set. The performance of the methods has been evaluated by testing the resulting active learning workflows in 3 diverse datasets: HIV-1 protease inhibitors, Taxol-derivatives and BRD4 inhibitors. The proposed strategies were successful in 80% of the cases for the taxol-derivatives and BRD4 inhibitors, while outperformed random selection in the case of the HIV-1 protease inhibitors time-split. Our results suggest that AL-COMBINE might be an effective way of producing consistently superior QSAR models with a limited number of samples. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10822-018-0181-3) contains supplementary material, which is available to authorized users.
has issue date	2018-12-18(xsd:dateTime)
bibo:doi	10.1007/s10822-018-0181-3
bibo:pmid	30564994
has license	no-cc
sha1sum (hex)	1b887fe8ffc197b720b6b470b746fdbbeb74b188
schema:url	https://doi.org/10.1007/s10822-018-0181-3
resource representing a document's title	Active learning strategies with COMBINE analysis: new tricks for an old dog
has PubMed Central identifier	PMC7087723
has PubMed identifier	30564994
schema:publication	J Comput Aided Mol Des
resource representing a document's body	covid:1b887fe8ffc197b720b6b470b746fdbbeb74b188#body_text
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