Tag Archives: machine learning

Highlights of 2023 (Part 2)

In this second and final installment of the ‘Highlights of 2023’ series, we give our readers a glance of another 3 most visited posts in this year. 

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Bio-QSARs: the inclusion of physiological trait information in machine learning QSARs allows predictions across species

In this blogpost, Jochen Zubrod talks about developing an innovative machine learning approach for ecotoxicity predictions. These cutting-edge models show impressive predictive power for acute pesticide toxicity in freshwater organisms, holding promise for applications in environmental risk assessment and pesticide research and development.

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Graphing Ecotoxicology

In this article, Jakob Wolfram talks about their recent publication “Graphing Ecotoxicology: The MAGIC graph for Linking Environmental Data on Chemicals”. This work detailed how a novel database structure was used to manage, aggregate, and harmonize different environmental databases in order to address large-scale environmental issues.

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