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

View ORCID ProfileAndreas Keller, Richard C. Gerkin, Yuanfang Guan, Amit Dhurandhar, Gabor Turu, Bence Szalai, Joel D. Mainland, Yusuke Ihara, Chung Wen Yu, Russ Wolfinger, Celine Vens, Leander Schietgat, Kurt De Grave, Raquel Norel, DREAM Olfaction Prediction Challenge Consortium, Gustavo Stolovitzky, Guillermo Cecchi, Leslie B. Vosshall, Pablo Meyer
doi: https://doi.org/10.1101/082495
Andreas Keller
1Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY 10065 USA
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  • ORCID record for Andreas Keller
Richard C. Gerkin
2School of Life Sciences, Arizona State University, Tempe, AZ 85281 USA
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Yuanfang Guan
3Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109 USA
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  • For correspondence: pmeyerr@us.ibm
Amit Dhurandhar
4IBM; TJ Watson, Computational Biology Center, Yorktown Heights, NY 10598 USA
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Gabor Turu
5Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest 1085 Hungary
6Laboratory of Molecular Physiology, MTA-SE, Budapest 1085 Hungary
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Bence Szalai
5Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest 1085 Hungary
6Laboratory of Molecular Physiology, MTA-SE, Budapest 1085 Hungary
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Joel D. Mainland
7Monell Chemical Senses Center, Philadelphia, PA 19104 USA
8Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104 USA
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Yusuke Ihara
7Monell Chemical Senses Center, Philadelphia, PA 19104 USA
9Institution for Innovation, Ajinomoto Co., Inc., Kawasaki, Kanagawa 210-8681 Japan
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Chung Wen Yu
7Monell Chemical Senses Center, Philadelphia, PA 19104 USA
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Russ Wolfinger
10SAS Institute, Inc., Cary, NC 27513 USA
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Celine Vens
11Department of Public Health and Primary Care, KU Leuven, Kulak, Kortrijk 8500, Belgium
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Leander Schietgat
12Department of Computer Science, KU Leuven, 3001 Leuven, Belgium
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Kurt De Grave
12Department of Computer Science, KU Leuven, 3001 Leuven, Belgium
13Flanders Make, 3920 Lommel, Belgium
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Raquel Norel
4IBM; TJ Watson, Computational Biology Center, Yorktown Heights, NY 10598 USA
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Gustavo Stolovitzky
4IBM; TJ Watson, Computational Biology Center, Yorktown Heights, NY 10598 USA
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Guillermo Cecchi
4IBM; TJ Watson, Computational Biology Center, Yorktown Heights, NY 10598 USA
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Leslie B. Vosshall
1Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY 10065 USA
14Howard Hughes Medical Institute, New York, NY, 10065 USA
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Pablo Meyer
4IBM; TJ Watson, Computational Biology Center, Yorktown Heights, NY 10598 USA
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  • For correspondence: pmeyerr@us.ibm
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Abstract

Despite 25 years of progress in understanding the molecular mechanisms of olfaction, it is still not possible to predict whether a given molecule will have a perceived odor, or what olfactory percept it will produce. To address this stimulus-percept problem for olfaction, we organized the crowd-sourced DREAM Olfaction Prediction Challenge. Working from a large olfactory psychophysical dataset, teams developed machine learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models predicted odor intensity and pleasantness with high accuracy, and also successfully predicted eight semantic descriptors (“garlic”, “fish”, “sweet”, “fruit”, “burnt”, “spices”, “flower”, “sour”). Regularized linear models performed nearly as well as random-forest-based approaches, with a predictive accuracy that closely approaches a key theoretical limit. The models presented here make it possible to predict the perceptual qualities of virtually any molecule with an impressive degree of accuracy to reverse-engineer the smell of a molecule.

One Sentence Summary Results of a crowdsourcing competition show that it is possible to accurately predict and reverse-engineer the smell of a molecule.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted October 21, 2016.
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Reverse-engineering human olfactory perception from chemical features of odor molecules
Andreas Keller, Richard C. Gerkin, Yuanfang Guan, Amit Dhurandhar, Gabor Turu, Bence Szalai, Joel D. Mainland, Yusuke Ihara, Chung Wen Yu, Russ Wolfinger, Celine Vens, Leander Schietgat, Kurt De Grave, Raquel Norel, DREAM Olfaction Prediction Challenge Consortium, Gustavo Stolovitzky, Guillermo Cecchi, Leslie B. Vosshall, Pablo Meyer
bioRxiv 082495; doi: https://doi.org/10.1101/082495
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Reverse-engineering human olfactory perception from chemical features of odor molecules
Andreas Keller, Richard C. Gerkin, Yuanfang Guan, Amit Dhurandhar, Gabor Turu, Bence Szalai, Joel D. Mainland, Yusuke Ihara, Chung Wen Yu, Russ Wolfinger, Celine Vens, Leander Schietgat, Kurt De Grave, Raquel Norel, DREAM Olfaction Prediction Challenge Consortium, Gustavo Stolovitzky, Guillermo Cecchi, Leslie B. Vosshall, Pablo Meyer
bioRxiv 082495; doi: https://doi.org/10.1101/082495

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