Lazar: a modular predictive toxicology framework
Abstract: lazar (lazy structure–activity relationships) is a modular framework for predictive toxicology. Similar to the read across procedure in toxicological risk assessment, lazar creates local QSAR (quantitative structure–activity relationship) models for each compound to be predicted. Model developers can choose between a large variety of algorithms for descriptor calculation and selection, chemical similarity indices, and model building. This paper presents a high level description of the lazar framework and discusses the performance of example classification and regression models
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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Frontiers in pharmacology. 4 (2013), 38, DOI 10.3389/fphar.2013.00038, issn: 1663-9812
IN COPYRIGHT http://rightsstatements.org/page/InC/1.0 rs
- Schlagwort
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QSAR
In silico-Methode
Semantic Web
Arzneimittelentwicklung
Arzneimitteldesign
- Ereignis
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Veröffentlichung
- (wo)
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Freiburg
- (wer)
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Universität
- (wann)
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2013
- Beteiligte Personen und Organisationen
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Fakultät für Mathematik und Physik
Physikalisches Institut
Albert-Ludwigs-Universität Freiburg
- DOI
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10.3389/fphar.2013.00038
- URN
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urn:nbn:de:bsz:25-freidok-119299
- Rechteinformation
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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25.03.2025, 13:57 MEZ
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Beteiligte
- Maunz, Andreas
- Gütlein, Martin
- Rautenberg, Micha
- Fakultät für Mathematik und Physik
- Physikalisches Institut
- Albert-Ludwigs-Universität Freiburg
- Universität
Entstanden
- 2013
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