The Bigger Fish: A Comparison of Meta-Learning QSAR Models on Low-Resourced Aquatic Toxicity Regression Tasks-Reference-Cited by-同舟云学术

The Bigger Fish: A Comparison of Meta-Learning QSAR Models on Low-Resourced Aquatic Toxicity Regression Tasks

Published:2023-06-14 Issue:46 Volume:57 Page:17818-17830
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Schlender Thalea¹²^ORCID,Viljanen Markus²,van Rijn Jan N.¹,Mohr Felix³,Peijnenburg Willie JGM.²⁴^ORCID,Hoos Holger H.¹⁵⁶,Rorije Emiel²,Wong Albert²

Affiliation:

1. Leiden Institute of Advanced Computer Science, Leiden University, Leiden 2333 CA, The Netherlands

2. National Institute for Public Health and the Environment (RIVM), Bilthoven 3720 BA, The Netherlands

3. Universidad de La Sabana, Chía 250001, Colombia

4. Institute of Environmental Sciences, Leiden University, Leiden 2333 CC, The Netherlands

5. Chair for AI Methodology, RWTH Aaachen University, Aachen 52056, Germany

6. Department of Computer Science, The University of British Columbia, Vancouver V6T 1Z4, Canada

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c00334

Reference54 articles.

1. QSAR Modeling: Where Have You Been? Where Are You Going To?

2. Principles of QSAR models validation: internal and external

3. Multispecies QSAR Modeling for Predicting the Aquatic Toxicity of Diverse Organic Chemicals for Regulatory Toxicology

4. Benfenati, E.; Manganaro, A.; Gini, G. C. VEGA-QSAR: AI Inside a Platform for Predictive Toxicology. Proceedings of the Workshop Popularize Artificial Intelligence co-located with the 13th Conference of the Italian Association for Artificial Intelligence (AI*IA 2013), Turin, Italy, December 5, 2013; pp 21–28.

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