
@eLife ambassador. PhD cand @KAISTPR @SeoulNatlUni. Working on drug promiscuity💊, extremophile trait genomics🪸🦈, & disease evolution👾. Naively pluripotent.
Daejeon, Republic of Korea
Joined October 2014
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Hot off the press 🔥! My co-first authored paper is out @ScienceAdvances!! A tour de force collab work with @new__hong @MethylAReum. We unlock for the first time the dog epigenome! 🐕 🧬 @SeoulNatlUni @je_yoel #ENCODE #epigenome #epigenetics #ScienceAdvancesResearch – at Gwanak-gu, Republic of Korea
Exciting news! Our lab’s latest paper in @ScienceAdvances on mapping the dog epigenome is out 🐶🧬! Close collaboration with my co-first authors @PrecursorCell + @MethylAReum! 🧵 👇(1/17) #ScienceResearch #ScienceAdvancesResearch #Epigenome
science.org/doi/10.1126/scia…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
Looking for a how-to blog on using RFD4-Proteina for protein design?
Start here:
developer.nvidia.com/blog/de…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
🧬 🤗 Nvidia just released a new protein design model, RFD4-Proteina, on @huggingface!
RFD4-Proteina has a thinking setting (like an LLM). At high thinking, it produces 76.40 usable designs per GPU-hour on a benchmark of 24 binding targets, where the next best method managed 13.2.
You can design protein sequences and all-atom structures together, conditioned on the molecular context you want to preserve: a binding target, an enzyme motif, a ligand, or selected structural features.
Thanks @nvidia and University of Washington's Institute for Protein Design for making the model open source and available on the Hub!
🧬 Try the model on the demo space: huggingface.co/spaces/nvidia…
🤗 Model: huggingface.co/nvidia/RFD4-P…
📖 Blog post: huggingface.co/blog/nvidia/r…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
AI+bio: the Escalante folks released a blog post yesterday, and as usual it's a banger, talking more about their multiplexed protein binding assay:
blog.escalante.bio/endless-p…
(I imagine this got lost amidst the securitypocalypse that landed yesterday.)
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
Derek Lowe mentioned my preprint in his "In the Pipeline" series which is very cool - big fan of his writing! science.org/content/blog-pos…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
We need to do experiments to figure out exactly how these work. But there are way too many candidates! So we created an explorable website (compass.arcinstitute.org/) and MCP (compass.arcinstitute.org/age…) for the research community to mine the COMPASS clusters and make their own discoveries!
Nature research paper: Divergent genomic evolution in astrocytomas and oligodendrogliomas
go.nature.com/4jjqax7
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
Today, our team is sharing a preprint on our new system for generative de-novo enzyme design, AlphaProtein Novo.
At @GoogleDeepMind, we have long focused on the building blocks of life (proteins). We developed AlphaFold to predict structure, trained language models to understand function, and built AlphaProteo to design de-novo binders. But proteins play many important roles in nature, such as enzymes that catalyze chemical reactions.
Designing entirely new enzymes from scratch to catalyze custom reactions has long been a holy grail for scientists. Our team has shown how AlphaProtein Novo can produce new-to-nature enzymes with state-of-the-art activity on 2 benchmark reactions. We’ve also designed custom enzymes to synthesize the pharmaceutical motif piperidine, and others to degrade the environmental plasticizer toxin DEHP.
While there is much more work to do in this direction, we’re excited to have demonstrated the ability to design functional proteins that go beyond what is known in nature. Huge congratulations to @jueseph, @ZvxyWu, Josh Abramson, the @GoogleDeepMind protein design team, and our collaborators in the @francesarnold & Liu Group! 🎉
🔗 Preprints and code:
biorxiv.org/content/10.64898…
biorxiv.org/content/10.64898…
github.com/google-deepmind/a…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
pH-sensitive binder design with Proton-PottsMPNN
biorxiv.org/content/10.64898…
An alluring display of cognitive surrender
🧬🌊 New preprint from our lab: DO1 Cas9, the first Cas9 nuclease characterised from the deep ocean — recovered from a metagenome at 1,500 m in the Atlantic.
❄️Cold-adapted: it cuts DNA efficiently at low temperature, where mesophilic SpCas9 retains only residual activity. 🧵1/4
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
We identified genes where exercise drove especially large shifts in DNA methylation. These methylation hotspots could serve as epigenetic markers of exercise.
@JoeEcker @GeraldineMaier @WuTsaiAlliance
cell.com/cell/abstract/S0092…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
Surviving on blood alone is no picnic. But a handful of genetic tweaks may have helped vampire bats evolve to become the only mammal known to feed exclusively on the stuff. sciencenews.org/article/vamp…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
Excited to share our new preprint! ChromE-seq reads 3D chromatin and gene expression in one cell. Across ~400,000 human primary cells, B lineage has the fewest chromatin loops and is most perturbed in trisomy 21, driving the B-cell block in Down syndrome.
biorxiv.org/content/10.64898…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
dsRNAscan maps human dsRNAome, revealing conservation, intermolecular dsRNA, and correlates of ADAR dependency dlvr.it/TVxNyy
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
We're also excited that our paper is accompanied by a Perspective in Science!
Many thanks to @s__ellis for highlighting our work and putting our findings into a broader context!
🔗 science.org/doi/10.1126/scie…
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
Beyond the obvious pocket: nature.com/articles/s41589-0…
Nature research paper: Early tetrapod neck mobility modelled using an extant analogue
go.nature.com/4i1OG3w
Mark Borris Aldonza (@precursorcell.bsky.social🦋) retweeted
1/5 Cryo-EM gives high-resolution RNA structures, but only when high Mg²⁺ freezes out their motion.
At physiological conditions, RNAs are dynamic and 3D reconstruction fails. Can we still learn their folding equilibria?
New preprint: yes, straight from the raw particle images👇




























