Author

Chung Wen Yu

Monell Chemical Senses CenterORCID 0000-0002-4596-5987Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Joel D. MainlandiD· 2 shared Richard C. GerkiniD· 2 shared Amit DhurandhariD· 1 shared Andreas KelleriD· 1 shared Bence SzalaiiD· 1 shared Brian K. LeeiD· 1 shared Celine VensiD· 1 shared Charles J. ArayataiD· 1 shared

Activity by Year

2017-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersNeuroscience

Joel D. MainlandORCID

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2 papers

Recent·Most cited

Drawing the Borders of Olfactory Space

Emily J. Mayhew, Charles J. Arayata, Richard C. Gerkin, Brian K. Lee, Jonathan M. Magill, Lindsey L. Snyder, Kelsie A. Little, Chung Wen Yu, Joel D. Mainland

The paper develops a model to predict odorous molecules based on chemical properties and estimates the number of possible odorous compounds to be over 30 billion.

Proceedings of the National Academy of Sciences · Apr 4, 2022Peer-reviewedNeuroscience

Reverse-engineering human olfactory perception from chemical features of odor molecules

Andreas Keller, Richard C. Gerkin, Yuanfang Guan, Amit Dhurandhar, Gábor Turu, Bence Szalai, Joel D. Mainland, Yusuke Ihara, Chung Wen Yu, Russell D. Wolfinger, Celine Vens, Leander Schietgat, Kurt De Grave, Raquel Norel, Gustavo A. Stolovitzky, , Pablo Meyer

The paper demonstrates that machine learning can accurately predict odor perception from molecular features, enabling reverse-engineering of smell.

Science · Feb 20, 2017Peer-reviewedNeuroscience