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Predicting Aromatic Amine Mutagenicity With Confidence: A Case Study Using Conformal Prediction
Swetox, Karolinska Institute, Unit of Toxicology Sciences, Södertälje, Sweden; Department of Computer and Systems Sciences, Stockholm University, Kista, Sweden.ORCID iD: 0000-0003-3107-331X
Leadscope, Columbus, USA.
AstraZeneca R&D Gothenburg, Mölndal, Sweden.
2018 (English)In: Biomolecules, E-ISSN 2218-273X, Vol. 8, no 3, article id 85Article in journal (Refereed) Published
Abstract [en]

The occurrence of mutagenicity in primary aromatic amines has been investigated using conformal prediction. The results of the investigation show that it is possible to develop mathematically proven valid models using conformal prediction and that the existence of uncertain classes of prediction, such as both (both classes assigned to a compound) and empty (no class assigned to a compound), provides the user with additional information on how to use, further develop, and possibly improve future models. The study also indicates that the use of different sets of fingerprints results in models, for which the ability to discriminate varies with respect to the set level of acceptable errors.

Place, publisher, year, edition, pages
MDPI, 2018. Vol. 8, no 3, article id 85
Keywords [en]
aromatic amines, confidence, conformal prediction, mutagenicity, random forest
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:oru:diva-83148DOI: 10.3390/biom8030085ISI: 000448394900043PubMedID: 30158463Scopus ID: 2-s2.0-85054765610OAI: oai:DiVA.org:oru-83148DiVA, id: diva2:1440459
Funder
Knut and Alice Wallenberg Foundation, 2013.0253Swedish Research Council, 2016-02031
Note

Forskningsfinansiär: National Institute of Environmental Health Sciences of the National Institutes of Health

Grant Number: R44ES026909

Available from: 2020-06-15 Created: 2020-06-15 Last updated: 2024-01-16Bibliographically approved

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Norinder, Ulf

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