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<feed xmlns="http://www.w3.org/2005/Atom"><title>UH Biocomputation Group - Graph neural networks</title><link href="http://biocomputation.herts.ac.uk/" rel="alternate"/><link href="http://biocomputation.herts.ac.uk/feeds/tags/graph-neural-networks.atom.xml" rel="self"/><id>http://biocomputation.herts.ac.uk/</id><updated>2023-02-23T08:57:15+00:00</updated><entry><title>Will Graph Neural Networks Revolutionise Computational Olfaction?</title><link href="http://biocomputation.herts.ac.uk/2023/02/23/will-graph-neural-networks-revolutionise-computational-olfaction-.html" rel="alternate"/><published>2023-02-23T08:57:15+00:00</published><updated>2023-02-23T08:57:15+00:00</updated><author><name>Michael Schmuker</name></author><id>tag:biocomputation.herts.ac.uk,2023-02-23:/2023/02/23/will-graph-neural-networks-revolutionise-computational-olfaction-.html</id><summary type="html">&lt;p class="first last"&gt;Michael Schmuker's Journal Club session where he will talk about a paper &amp;quot;Will Graph Neural Networks Revolutionise Computational Olfaction?&amp;quot;&lt;/p&gt;
</summary><content type="html">&lt;p&gt;This week on Journal Club session Michael Schmuker will talk about a paper &amp;quot;Will Graph Neural Networks Revolutionise Computational Olfaction?&amp;quot;.&lt;/p&gt;
&lt;hr class="docutils" /&gt;
&lt;p&gt;How to predict the smell of a molecule given it's chemical structure? A group
of researchers around Google's Alex Wiltschko have used Graph Neural Networks
(GNN) to develop apparently outperform previous approaches to predict the smell
of an odorant [1]. They proposed the &amp;quot;Principal Odor Map&amp;quot; (POM): a latent space
which GNN learn from a data set of several thousand odorants. They show how the
POM improves prediction of scent [2], how it aligns with metabolic pathways
producing odors [3], and how it gives rise to the design of new mosquito
repellents [4]. The group has now launched a computational olfaction startup
[5]. In my talk I will introduce the GNN method and their approach to produce
the POM, summarise their results, and discuss how the performance of their
model compares to other established methods.&lt;/p&gt;
&lt;p&gt;In my talk I will introduce the GNN method and their approach to produce the
POM, summarise their results, and discuss how the performance of their model
compares to other established methods.&lt;/p&gt;
&lt;div class="line-block"&gt;
&lt;div class="line"&gt;&lt;br /&gt;&lt;/div&gt;
&lt;/div&gt;
&lt;p&gt;Papers:&lt;/p&gt;
&lt;ul class="simple"&gt;
&lt;li&gt;[1] B. Sanchez-Lengeling, J. Wei, B. Lee, R. Gerkin, A. Aspuru-Guzik, A.
Wiltschko, &lt;a class="reference external" href="http://arxiv.org/abs/1910.10685"&gt;&amp;quot;Machine Learning for Scent: Learning Generalizable Perceptual
Representations of Small Molecules&amp;quot;&lt;/a&gt;, 2019, arXiv,&lt;/li&gt;
&lt;li&gt;[2] B. Lee, E. Mayhew, B. Sanchez-Lengeling, J. Wei, W. Qian, K. Little, M.
Andres, B. Nguyen, T. Moloy, J. Parker, R. Gerkin, J. Mainland, A. Wiltschko,
&lt;a class="reference external" href="https://doi.org/10.1101/2022.09.01.504602"&gt;&amp;quot;A Principal Odor Map Unifies Diverse Tasks in Human Olfactory Perception&amp;quot;&lt;/a&gt;, 2022,&lt;/li&gt;
&lt;li&gt;[3] W. Qian, J. Wei, B. Sanchez-Lengeling, B. Lee, Y. Luo, M. Vlot, K. Dechering,
J. Peng, R. Gerkin, A. Wiltschko, &lt;a class="reference external" href="https://doi.org/10.1101/2022.07.21.500995"&gt;&amp;quot;Metabolic Activity Organizes Olfactory
Representations&amp;quot;&lt;/a&gt;, 2022,&lt;/li&gt;
&lt;li&gt;[4] J. Wei, M. Vlot, B. Sanchez-Lengeling, B. Lee, L. Berning, M. Vos, R.
Henderson, W. Qian, D. Ando, K. Groetsch, R. Gerkin, A. Wiltschko, K.
Dechering, &lt;a class="reference external" href="https://doi.org/10.1101/2022.09.01.504601"&gt;&amp;quot;A Deep Learning and Digital Archaeology Approach for Mosquito
Repellent Discovery&amp;quot;&lt;/a&gt;, 2022,&lt;/li&gt;
&lt;li&gt;[5] &lt;a class="reference external" href="https://osmo.ai/"&gt;&amp;quot;https://osmo.ai/&amp;quot;&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Date:&lt;/strong&gt;  2023/02/24 &lt;br /&gt;
&lt;strong&gt;Time:&lt;/strong&gt; 14:00 &lt;br /&gt;
&lt;strong&gt;Location&lt;/strong&gt;: online&lt;/p&gt;
</content><category term="Seminars"/><category term="Deep learning"/><category term="Graph neural networks"/><category term="Olfaction"/></entry></feed>