https://doi.org/10.7490/f1000research.1111090.1
Slides
NOT PEER REVIEWED
Download
metrics
VIEWS
220
 
downloads
15
CITE
How to cite these slides:
Gerkin RC. From shape to smell: predicting olfactory perceptual descriptors using molecular structural information [version 1; not peer reviewed]. F1000Research 2015, 4:1381 (slides) (https://doi.org/10.7490/f1000research.1111090.1)
NOTE: it is important to ensure the information in square brackets after the title is included in this citation.

From shape to smell: predicting olfactory perceptual descriptors using molecular structural information

Author Affiliations
  • Metrics
  • 220 Views
  • 15 Downloads
Browse by related subjects
Published 30 Nov 2015

From shape to smell: predicting olfactory perceptual descriptors using molecular structural information

[version 1; not peer reviewed]

Author Affiliations
1 Arizona State University, USA
Presented at
8th Annual RECOMB/ISCB Conference on Regulatory and Systems Genomics, with DREAM Challenges 2015
Abstract
Competing Interests

No competing interests were disclosed

Keywords
Olfaction, Smell, Machine Learning, Random Forest, Prediction, Human, Psychophysics, Statistics
Comments
0 Comments
 
Sign In
If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password.

The email address should be the one you originally registered with F1000.

Email address not valid, please try again

You registered with F1000 via Google, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Google account password, please click here.

You registered with F1000 via Facebook, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Facebook account password, please click here.

Code not correct, please try again
Email us for further assistance.
Server error, please try again.