Predicting human olfactory perception from chemical features of odor molecules-Reference-Cited by-同舟云学术

Predicting human olfactory perception from chemical features of odor molecules

Published:2017-02-24 Issue:6327 Volume:355 Page:820-826
ISSN:0036-8075
Container-title:Science
language:en
Short-container-title:Science

Author:

Keller Andreas¹,Gerkin Richard C.²^ORCID,Guan Yuanfang³^ORCID,Dhurandhar Amit⁴^ORCID,Turu Gabor⁵⁶^ORCID,Szalai Bence⁵⁶^ORCID,Mainland Joel D.⁷⁸^ORCID,Ihara Yusuke⁷⁹^ORCID,Yu Chung Wen⁷^ORCID,Wolfinger Russ¹⁰^ORCID,Vens Celine¹¹,schietgat leander¹²^ORCID,De Grave Kurt¹²¹³,Norel Raquel⁴^ORCID,Stolovitzky Gustavo⁴¹⁴^ORCID,Cecchi Guillermo A.⁴^ORCID,Vosshall Leslie B.¹¹⁵^ORCID,meyer pablo⁴¹⁴^ORCID,

Affiliation:

1. Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY 10065, USA.

2. School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA.

3. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.

4. Thomas J. Watson Computational Biology Center, IBM, Yorktown Heights, NY 10598, USA.

5. Department of Physiology, Faculty of Medicine, Semmelweis University, 1085 Budapest, Hungary.

6. Laboratory of Molecular Physiology, Hungarian Academy of Science, Semmelweis University (MTA-SE), 1085 Budapest, Hungary.

7. Monell Chemical Senses Center, Philadelphia, PA 19104, USA.

8. Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA.

9. Institution for Innovation, Ajinomoto Co., Inc., Kawasaki, Kanagawa 210-8681, Japan.

10. SAS Institute, Inc., Cary, NC 27513, USA.

11. Department of Public Health and Primary Care, KU Leuven, Kulak, 8500 Kortrijk, Belgium.

12. Department of Computer Science, KU Leuven, 3001 Leuven, Belgium.

13. Flanders Make, 3920 Lommel, Belgium.

14. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

15. Howard Hughes Medical Institute, New York, NY 10065, USA.

Abstract

How will this molecule smell? We still do not understand what a given substance will smell like. Keller et al. launched an international crowd-sourced competition in which many teams tried to solve how the smell of a molecule will be perceived by humans. The teams were given access to a database of responses from subjects who had sniffed a large number of molecules and been asked to rate each smell across a range of different qualities. The teams were also given a comprehensive list of the physical and chemical features of the molecules smelled. The teams produced algorithms to predict the correspondence between the quality of each smell and a given molecule. The best models that emerged from this challenge could accurately predict how a new molecule would smell. Science , this issue p. 820

Funder

National Institutes of Health

Howard Hughes Medical Institute

National Center for Advancing Translational Sciences

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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