Eighteen teams participated in an IBM Research Dialogue for Reverse Engineering Assessments and Methods (DREAM) challenge to develop algorithms that can estimate how humans will perceive a particular odor from its molecular properties.
Rockefeller University's Andreas Keller compiled a dataset of odor perceptions, specifying more than 4,800 molecular characteristics for each compound.
The challenge's goal was designing the best model from data on 69 smells to anticipate their scent profiles.
A linear-model algorithm placed second by taking different parts of each molecule and predicting how each bit would smell. IBM Research's Pablo Meyer suggests this may reflect something basic concerning olfaction and how odors interact with receptors. Meyer says instead of an entire molecule matching a distinct receptor, perhaps it engages with numerous receptors, each of which responds to these molecular subunits.
"A nice step would be to see how that relates to the binding of odor molecules to odor receptors," he notes.
From The Scientist
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