
Using Deep Learning to Predict the Olfactory Properties of Molecules - dyslexit
https://ai.googleblog.com/2019/10/learning-to-smell-using-deep-learning.html
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jaredtn
Summary:

\- They created an entirely new dataset of ~5000 molecules, all hand-labeled
by perfume experts.

\- They held a competition (presumably Kaggle or a similar platform) to
classify this dataset, and used the results as a strong baseline.

\- Their GNNs get comparable (slightly better, but not statistically
significant) results than the winning random forest model of the competition.

The embeddings show promise, but I'm curious why they omitted a simple "fully
connected layer" on the Morgan bit descriptors as a baseline classifier. Seems
like that would outperform the random forest.

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hooloovoo_zoo
The baseline isn't that strong tbh, it's from a very small competition from a
long time ago.
[https://www.synapse.org/#!Synapse:syn2811262/wiki/78388](https://www.synapse.org/#!Synapse:syn2811262/wiki/78388)

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phonebucket
Graph convolutional networks are really cool and widely applicable. The
fastest intro to the field me was actually not a paper or blog post, but the
docs of Pytorch Geometric. The definition of their message passing framework
[0] gets you to the right frame of mind, after which there are well documented
and cited implementations of various papers which you can reuse [1].

[0] [https://pytorch-
geometric.readthedocs.io/en/latest/notes/cre...](https://pytorch-
geometric.readthedocs.io/en/latest/notes/create_gnn.html)

[1] [https://pytorch-
geometric.readthedocs.io/en/latest/modules/n...](https://pytorch-
geometric.readthedocs.io/en/latest/modules/nn.html)

~~~
kevin948
Neat. Can you point to any particularly compelling applications? I'm looking
into a graph representation for something myself and this looks incredibly
helpful.

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phonebucket
The applications that speak to me most are those involving predicting
properties of molecules, and also properties of biochemical networks, though I
appreciate that’s not what many others would find compelling! Sorry not to be
of more help.

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ArtWomb
>>> it should be possible to directly predict the end sensory result of an
input molecule, even without knowing the intricate details of all the systems
involved

Maybe we're missing the most interesting aspect. Olfactory Receptor Genes in
humans comprise ~1% of the total genome. The benefit here is in understanding
how environmental changes trigger beneficial mutations and enhance sensory
features.

[https://en.wikipedia.org/wiki/Evolution_of_olfaction](https://en.wikipedia.org/wiki/Evolution_of_olfaction)

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ramraj07
I doubt the olfactory complex evolves via simple mutations directly on the
receptors, but rather on other dna constructs that can quickly (and badly)
replicate genes like retrotransposons

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dekhn
if anybody could answer questions like that definitely, it would be a great
advance. There is fairly strong evidence that olfaction evolution occurs by
gene duplication followed by selection.

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mywittyname
This is quite similar to a project that we did in college as part of a
introduction to data science course. The professor built a sensor using an
array of different smoke detectors, then pumped air over different liquids
(coffee, Coke, OJ, etc) then through the sensor array, capturing the signal
strength in a text document. We used different classification techniques to
determine the composition of unknown liquids.

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Pick-A-Hill2019
I know I may regret saying this* but have they considered
vaporising/heating/burning the air sample to produce a spectrograph and then
running an image recognition for comparison to known smells. A bit like you
can produce a spectrograph of an mp3 and get an almost instantaneous hit if
the track is previously known. Subtract out the known smells and the remaining
is an unknown. Find similar shaped molecules and return their likely traits
(musky, floral, almonds etc.) with a visual keyword cloud.

It is two different things – you either recognize a scent OR you identify a
scent. Why not speed things up by running it as a two step process? Recognize
= Rapid results, Identify = Best Guess at what it might smell like. I’m not
sure how a human determines that there is a smell of gasoline, freshly cut
grass and a hint of something else/unknown in the air rather than thinking
hmmm, I do not recognize a scent that has aspects of cut grass AND gasoline
AND an unknown therefore the whole scent is ‘unknown’.

*anon-experts that go ‘gosh, why didn’t those idjuts with multiple PhDs think of that’

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Terr_
I think a spectrograph tells you more about the constituent elements in the
sample, instead of the various shapes of various molecules that existed before
you heated it.

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kevin948
Interesting point. Are there sensors/tools other than a spectrograph that
could help? Some clever use of a camera or something?

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Reelin
I won't claim it's impossible, but... olfaction boils down to a small molecule
protein interaction, similar to drug discovery. The scales in question are
_far_ too small for typical imaging devices; these objects are far smaller
than the wavelength of visible light. CryoEM and X-ray diffraction are used in
these domains, but don't apply in the manner you appear to have in mind. I
suppose CryoEM technically counts as "clever use of a camera" though.

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mynegation
When I was a teenager and was interested in chemistry 30 years ago, the
question that bothers me all the time if it is possible to predict physical
characteristics such as color, phase diagrams, and - yes - smell from chemical
composition and structure. Tried to do that with pen and paper, but did not
get much farther that acids smell acidic and alkali smell alkaline, and salts
largely do not smell unless they easily dissociate. I quickly realized that
the most interesting part of this problem is in organic compounds but that was
well beyond my reach. Thinking about it now I am wondering about the choice of
“variables”. To me it looks like we are trying to describe complex smells in
terms of combination of other probably also complex smells. Is it the right
base? If I were researching that I would try to find the bases - either
chemical compounds with the simplest structure, like benzol, or compounds that
trigger the minimal number of receptors and different and disjoint sets of
receptors at that. Is there any research in that area?

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kevin948
I like it. I wonder if any faux meat companies are doing things like this?

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adrianmonk
It's a little surprising to me (not necessarily bad, just unexpected) that
Google is researching this.

Yes, it's good for companies to do some R&D, and sometimes the R part of the
R&D gets pretty theoretical, which is usually a good sign that a company is
trying to really innovate.

But usually also there's some indirect way to tie it back to some kind of
application that could possibly somehow make the company money in the long
term. Otherwise, you're just a for-profit company spending money on something
because it's interesting.

So what's the application here? Are there novel ideas or techniques here that
can be applied to other AI problems? Is there some kind of application for
smell in a Google product?

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dekhn
Google invests fairly heavily into research and there is a fair amount of
freedom among engineers and researchers to do projects with Google resources,
even when there is no direct product application.

For example, I ran an idle-cycle-harvesting service at Google called Exacycle
that ran problems like protein folding, protein design, drug discovery,
telescope discovery, and more. The only pushback I got was to run problems
where the results could reasonably be considered "useful" (scientifically).

One way to think about it is that many of the people with power at Google
really like science and have the resources to support it. Once you've built
things like TPUs, it would be a waste not to dedicate some about of their
resources to problems that people wouldn't be able to address.

Another way to think about it is these things have indirect effects- even if
Google didn't want to make some sort of product with smell (like a phone with
a builtin GC-MS?), publishing this work gets the attention of scientists, who
will then read the paper, and consider Google Cloud as a place they'd like to
do their work.

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colorincorrect
unrelated: but there's a theory that the sense of smell is actually
influenced/determined by quantum effects. see this:

[https://en.wikipedia.org/wiki/Vibration_theory_of_olfaction](https://en.wikipedia.org/wiki/Vibration_theory_of_olfaction)

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perl4ever
I read Luca Turin's book, "The Secret of Scent", years ago, and it certainly
seemed engaging. Reviews on Amazon seem to be mixed.

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pmoriarty
I wonder if a similar technique could be used to predict a molecule's
psychedelic potential.

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std_throwaway
How would you quantify that?

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ribrars
Great question, one could use existing known chemicals as a starting point.
There could be a potential to use fMRI readings on a model organism in
realtime to generate data.

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kevin948
Compelling. I wonder what else this could be applied to in addition to
psychedelics? Anti-anxiety and other sensory affecting drugs?

If you wanna get Black Mirror-esque, perhaps a Soma-like medication from Brave
New World (essentially pacifies/zombifies you by creating endless bliss) could
be made. Or the "bliss" drug episode of Doctor Who.

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ende
Deep Smelling

