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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Benchmarking Transcriptomics Foundation Models for Perturbation Analysis : one PCA still rules them all · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2410.13956/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2410.13956/feed.xml" rel="self" type="application/rss+xml" /><item><title>Benchmarking Transcriptomics Foundation Models for Perturbation Analysis : one PCA still rules them all — mentioned by donovanr</title><link>https://news.ycombinator.com/item?id=44325592</link><guid isPermaLink="false">urn:hackerpapers:mention:2410.13956:44325592</guid><pubDate>Fri, 20 Jun 2025 08:01:10 GMT</pubDate><description>&lt;p&gt;Yes, this. A lot of work in this field is missing from that timeline. Just circa 2010-2020, Les Loew&amp;#x27;s VCell 3D PDE approaches, Faeder et al.&amp;#x27;s BioNetGen / ODE work, Luthey-Schulten Shulten&amp;#x27;s grid based cell models, the Pittsburgh supercomputing center&amp;#x27;s 3D monte-carlo MCell, the image-based deep learning models at the Allen Institute for Cell Science... It&amp;#x27;s nice to see the idea of virtual cells make a comeback now, though the meaning seems to have shifted to transciptomics-based transformer / gpu-powered models (which have issues[0]), it&amp;#x27;s a fun field / problem, but I think it will make…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2410.13956/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
