enviPath is both, a database and a prediction system, for the microbial biotransformation of organic environmental contaminants. The database provides the possibility to store and view experimentally observed biotransformation pathways, and supports annotating pathways with experimental and environmental conditions. The pathway prediction system provides different relative reasoning models to predict likely biotransformation pathways and products.

enviPath is a joint project with Eawag and the spin-off company enviPath,


Dost, Katharina; Tam, Jason; Lorsbach, Tim; Schmidt, Sebastian; Wicker, Jörg

Defining Applicability Domain in Biodegradation Pathway Prediction Unpublished Forthcoming


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Hafner, Jasmin; Lorsbach, Tim; Schmidt, Sebastian; Brydon, Liam; Dost, Katharina; Zhang, Kunyang; Fenner, Kathrin; Wicker, Jörg

Advancements in Biotransformation Pathway Prediction: Enhancements, Datasets, and Novel Functionalities in enviPath Unpublished Forthcoming


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Dost, Katharina; Pullar-Strecker, Zac; Brydon, Liam; Zhang, Kunyang; Hafner, Jasmin; Riddle, Pat; Wicker, Jörg

Combatting over-specialization bias in growing chemical databases Journal Article

In: Journal of Cheminformatics, vol. 15, iss. 1, pp. 53, 2023, ISSN: 1758-2946.

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Tam, Jason; Lorsbach, Tim; Schmidt, Sebastian; Wicker, Jörg

Holistic Evaluation of Biodegradation Pathway Prediction: Assessing Multi-Step Reactions and Intermediate Products Journal Article

In: Journal of Cheminformatics, vol. 13, no. 1, pp. 63, 2021.

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Stepišnik, Tomaž; Škrlj, Blaž; Wicker, Jörg; Kocev, Dragi

A comprehensive comparison of molecular feature representations for use in predictive modeling Journal Article

In: Computers in Biology and Medicine, vol. 130, pp. 104197, 2021, ISSN: 0010-4825.

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Latino, Diogo; Wicker, Jörg; Gütlein, Martin; Schmid, Emanuel; Kramer, Stefan; Fenner, Kathrin

Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data Journal Article

In: Environmental Science: Process & Impact, 2017.

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Wicker, Jörg; Fenner, Kathrin; Kramer, Stefan

A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction Book Section

In: Lässig, Jörg; Kersting, Kristian; Morik, Katharina (Ed.): Computational Sustainability, pp. 75-97, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-31858-5.

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Wicker, Jörg; Lorsbach, Tim; Gütlein, Martin; Schmid, Emanuel; Latino, Diogo; Kramer, Stefan; Fenner, Kathrin

enviPath – The Environmental Contaminant Biotransformation Pathway Resource Journal Article

In: Nucleic Acid Research, vol. 44, no. D1, pp. D502-D508, 2016.

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Wicker, Jörg

Large Classifier Systems in Bio- and Cheminformatics PhD Thesis

Technische Universität München, 2013.

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Wicker, Jörg; Fenner, Kathrin; Ellis, Lynda; Wackett, Larry; Kramer, Stefan

Predicting biodegradation products and pathways: a hybrid knowledge- and machine learning-based approach Journal Article

In: Bioinformatics, vol. 26, no. 6, pp. 814-821, 2010.

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Wicker, Jörg; Fenner, Kathrin; Ellis, Lynda; Wackett, Larry; Kramer, Stefan

Machine Learning and Data Mining Approaches to Biodegradation Pathway Prediction Proceedings Article

In: Bridewell, Will; Calders, Toon; Medeiros, Ana Karla; Kramer, Stefan; Pechenizkiy, Mykola; Todorovski, Ljupco (Ed.): Proceedings of the Second International Workshop on the Induction of Process Models at ECML PKDD 2008, 2008.

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