Structural biologist and biochemist. CNRS researcher at CBM Orléans. Interested in protein modifications & interactions. Also husband, dad of 3, friend, ☧.

Orléans, France
Joined August 2020
Marcin J. Suskiewicz retweeted
[HOMMAGE] Le CNRS a appris avec une grande tristesse le décès de Pierre Joliot, pionnier de la photosynthèse et figure de la recherche au CNRS. Nos condoléances à sa famille et à ses proches. 👉 insb.cnrs.fr/fr/cnrsinfo/hom…
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Marcin J. Suskiewicz retweeted
Daniel Litt
@littmathSep 30
The vibe on here re: AIxMath is kind of apocalyptic, and what’s true is that highly capable AI models have significant impacts on (non-mathematical!) questions around hiring, journals, etc. But if you just log off in fact the day to day of doing math research is really not so different, except that you can talk to your computer about it and sometimes it’s helpful. What does this help look like? In practice high quality math research has never looked like “run a for loop through open conjectures and try to resolve them all,” and it still doesn’t. Most interesting work does not have the form of a problem set, but is rather an open-ended exploration of some phenomenon. There are lots of ways talking to one’s computer can help with this, but I don’t feel particularly worried that it will be automated. After all, it’s a process that is only done when I say it is! Anyway, it’s a great time to be a congenitally calm mathematician.
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Marcin J. Suskiewicz retweeted
People on this app don't appreciate how well purely human mathematics is doing. People prove major results literally every few weeks, with proofs that are insightful, beautiful, and solve many problems simultaneously. Currently reading this wonderful thing: arxiv.org/pdf/2608.26392
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Marcin J. Suskiewicz retweeted
#100ANS #15SEPTEMBRE2026 Mon père, le #mathématicien #JeanPierreSerre , + jeune médaille Fields à 27ans, prix Abel, médaille d'or du @CNRS, élu prof. au Collège de France à 29ans, racontera le 15 septembre 2026, jour de ses 100ans, ses souvenirs #mathématiques à l'institut Henri Poincaré. #sciences @cdf1530 @InHenriPoincare @abel_prize @Michel_Broue
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Marcin J. Suskiewicz retweeted
If your claim to fame is pushing a button to optimize a breakthrough announced by a junior mathematician a few days ago, it’s not very impressive, to put it politely. Without getting into rumors on the sequence of events…
1/ ✨ World record today on bounded gaps between primes, one of number theory’s oldest open conjectures.  We show that infinitely many pairs of prime numbers are separated by 212 or less.
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Marcin J. Suskiewicz retweeted
Btw Andreas Thom is now also wondering outloud whether OpenAI used his personal user data to train the model to find a non-sofic group... mathstodon.xyz/@andreasthom/…
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Marcin J. Suskiewicz retweeted
This reference list for Navier Stokes blowup is outrageous. No Chen-Hou, no Alpoge-Buckmaster, no Córdoba and Martínez-Zoroa, no Elgindi. They are not properly attributing any previous work to the problem
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Marcin J. Suskiewicz retweeted
I'm pleased to share our review on how Human Herpesviruses (HHVs) interact with the host SUMOylation machinery. We discuss viral strategies, molecular mechanisms, and key open questions. Read more: sciencedirect.com/science/ar… #Virology #Herpesvirus #SUMOylation #HHVs
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Marcin J. Suskiewicz retweeted
Still, there are norms in the profession aimed at avoiding the most egregious infractions: You don’t step into other people’s lanes when you don’t have something genuinely new to offer. 29/
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Marcin J. Suskiewicz retweeted
My prediction from last summer was that the number of frontier AI models getting a gold medal at this summer’s IMO will be… zero! The reason is that they won’t bother to compete, it’ll simply be beneath them. If anyone can now push a button on Codex / Claude Code and get a perfect score, what’s the point? No, they’ll just leave the 17 year olds to take the test on their own. (The open source models will still compete for another year or so. That’s my guess!) Similarly, I think the labs pushing “research math” is also a fad that will expire soon enough. Think about it. GPT solved a major problem (Erdos unit distance); what they’re not reporting is the 1000 other problems they attacked and failed to make progress. [That’s not exactly deception; I also don’t report the dozens of things I tried to prove and failed…] They’re also not reporting the millions of dollars all of this cost them, and for what? Right now the “for what” is advertising: they’re signaling that they’re the best model for math, so you should use them for whatever your reasoning task is. Math departments also spend millions of dollars and produce theorems, but that is their actual end goal. A tech company is happy with a million-dollar theorem only if it predicts a billion-dollar application somewhere else. Once the bubble bursts, investors will want “real” applications from AI, new drugs, self driving / flying cars, etc etc. Nobody will care that the systems are also useful at proving theorems. Nobody but us mathematicians. So like the IMO, I think the frontier labs will get bored of theorems, and will leave us humans alone to keep doing math (and they’ll give us an amazing tool with which to do it!). Does that make sense? What do you think?
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Marcin J. Suskiewicz retweeted
This thread highlights what I fear will be the degradation of human knowledge due to AI. If I were being charitable, I would say that here Gemini is playing a hybrid role of textbook and tutor, where your tutor has a photographic memory and world class speed reading abilities, but might not be smart enough to get that PhD. So sure, access to that type of tutor is infinitely better than reading baby Rudin in a vacuum. But there is no way AI here is replacing Rudin. Unfortunately though, to a lot of people, it gives the illusion of being better while actually being worse. And thus people will think they are learning more when they are actually learning less.
Math textbooks are written in a pointlessly obtuse way. Gemini does an incomparably better job. My professional opinion is that all undergrads learning real analysis should give up reading baby Rudin, and simply learn analysis from Gemini instead
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Marcin J. Suskiewicz retweeted
Triple Self-Portrait. 1960. Norman Rockwell.
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Marcin J. Suskiewicz retweeted
Our recent article in Journal of Molecular Biology explores how Post-Translational Modifications (PTMs) orchestrate the repair of trapped Topoisomerase-induced DNA breaks via TDP1 and TDP2. sciencedirect.com/.../pii/S0… @iacskolkata @IndiaDST @ICMRDELHI @DBTIndia
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I’m happy to share our recent manuscript in which we are structurally and biochemically investigating 3'-5' tRNA splicing ligases, including a #cryoEM structure of the five-subunit D. rerio tRNA ligase complex. jbc.org/article/S0021-9258(2…
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Marcin J. Suskiewicz retweeted
Thèse en glycochimie disponible dans notre équipe @ICOA_UMR7311 @Univ_Orleans @CNRSchimie @AgenceRecherche Si vous êtes intéressés, merci de postuler via le portail ADUM à cette adresse : collegedoctoral-cvl.fr/as/ed…
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Marcin J. Suskiewicz retweeted
What a heartening and inspiring thing to come across at the end of my walk to a meeting @UniofOxford.
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Marcin J. Suskiewicz retweeted
Our perspective on Hsp90 as a global modifier of the genotype-phenotype-fitness map, along with its implications for evolution in nature and clinical settings, is now out in JMB. We review the existing literature, identify open questions, contextualize our recent findings on Hsp90, and present new analyses that expand the current understanding of its evolutionary impact. Congrats to @jaguilarrod and Chris Jakobson. Check it out here: sciencedirect.com/science/ar…
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Marcin J. Suskiewicz retweeted
GPUs are *fast* at aligning protein sequences (and profiles!). 178x faster than JackHMMER! In ColabFold, 23x faster end-to-end compared to AlphaFold2 reaching the same accuracy! You get immediate speedups for all methods leveraging MSAs, from DCA, to PoET, and even AlphaFold3!
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Marcin J. Suskiewicz retweeted
Excited to share that the AlphaFold 3 model code and weights are now available for academic use. Looking forward to seeing what new research this unlocks and how the research community builds on AlphaFold 3 for scientific discoveries github.com/google-deepmind/a… 1/2
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