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hbkgenomics.bsky.social

@hbkgenomics.bsky.social
141 followers 59 following 10 posts

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Terence Tao @teorth.bsky.social · 11/09/2026
A group of 25 Fields Medalists, including myself, have made a joint declaration on Math and AI: mathandai.org . We welcome additional signatories. See also this article in the Economist announcing the declaration: www.economist.com/science-and-...
mathandai.org
Declaration — Math and AI
Read the declaration and add your name.
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 26/08/2026
Foldseek-Interface enables fast search/clustering of the protein interface universe! We clustered 3.1M PDB dimers into 77,167 groups and found new interfaces keep appearing even as fold discovery plateaus. 🧵 📄 www.biorxiv.org/content/10.6... 🔎 search.foldseek.com/interface 🌐 interface.foldseek.com
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RSG Korea @rsg-korea.bsky.social · 11/08/2026
🎉 RSG-Korea 2026 1st Community Meetup Bioinformatics & computational biology students/ECRs, join us for networking, career talks & food! 🍪 📅 Aug 28, 13:00–18:00 📍 Yonsei University 🎤 Postdoc Talk Junhyung Cha (Harvard) Dongwook Kim (Lausanne) 👉 Register here: docs.google.com/forms/d/e/1F...
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 01/08/2026
Riboseek is a fast RNA/DNA search. More sensitive than nhmmer at 250x speed. Structure-aware realignment produces MSAs approaching rMSA quality. Plus 1.7M precomputed RNA MSAs, and an API to search your own 📄 www.biorxiv.org/content/10.6... 💾 github.com/steineggerla... 🌐 search.foldseek.com/riboseek
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Kate Michie @kmichie.bsky.social · 19/06/2026
Great summary and insight into Folddisco. 🧶🧬
linkedin.com
Folddisco and the Hidden Cost of Thinking at the Wrong Resolution
Data‑Rich, Insight‑Poor? —LXXIX Kim et al.’s Folddisco paper is easy to misread.
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 19/06/2026
ICML is happening in Seoul this year, and I’ve been getting several messages about lab visits. Who else will be in town and would like to meet? @milot.bsky.social lab and mine are planning a dinner on July 7th, after the reception. Let me know if you’re interested!
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hbkgenomics.bsky.social @hbkgenomics.bsky.social · 06/06/2026
Does your designed active site already exist in nature? Is an uncharacterized protein hiding a catalytic site or a pocket? Folddisco answers both, searching millions of structures for a 3D motif in seconds. @natbiotech.nature.com 🧬 📄 www.nature.com/articles/s41... 🧵1/7👇
nature.com
Structural motif search across the protein universe with Folddisco - Nature Biotechnology
Folddisco enables protein structural motif search in million scale databases.
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Nature Biotechnology @natbiotech.nature.com · 05/06/2026
Structural motif search across the protein universe with Folddisco - @martinsteinegger.bsky.social go.nature.com/4g8lCb0
go.nature.com
Structural motif search across the protein universe with Folddisco - Nature Biotechnology
Folddisco enables protein structural motif search in million scale databases.
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 06/06/2026
Meet the Folddisco Marv, designed by Hyunbin Kim, who also developed Folddisco.
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 06/06/2026
Folddisco is now published @natbiotech.nature.com. It’s a fast motif search for similar 3D DISCOntinuous residues like catalytic sites or zinc fingers across the entire protein universe. 📄 www.nature.com/articles/s41... 💾 folddisco.foldseek.com​​​​​​​​​​​​​​​​ 🌐 search.foldseek.com/folddisco
nature.com
Structural motif search across the protein universe with Folddisco - Nature Biotechnology
Folddisco enables protein structural motif search in million scale databases.
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jingiyeo.bsky.social @jingiyeo.bsky.social · 03/04/2026
45 novel protein folds in the updated AFESM (AFDB + ESMatlas) manuscript: • 12 high-confidence folds in AFESM • 33 by ColabFold-repredicting 2.3M low-quality domains We show AFDB captures most domains already and ESMfold struggles with novelty 🌏 afesm.foldseek.com 📄 biorxiv.org/content/10.1...
afesm.foldseek.com
AFESM Clusters
Foldseek clustered 820M AlphaFold DB + ESMatlas structures
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Milot Mirdita @milot.bsky.social · 20/01/2026
My time in @martinsteinegger.bsky.social's group is ending, but I’m staying in Korea to build a lab at Sungkyunkwan University School of Medicine. If you or someone you know is interested in molecular machine learning and open-source bioinformatics, please reach out. I am hiring! mirdita.org
mirdita.org
Mirdita Lab - Laboratory for Computational Biology & Molecular Machine Learning
Mirdita Lab builds scalable bioinformatics methods.
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 22/10/2025
End-to-end protein design in the browser through evedesign. Generate and interactively explore designs in 2D/3D and export them as codon-optimized DNA. The underlying open source framework (released soon) is build to easily add new methods, more on that soon. 🌐 evedesign.bio
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bioRxiv Bioinfo @biorxiv-bioinfo.bsky.social · 07/08/2025
Protein Structure Informed Bacteriophage Genome Annotation with Phold www.biorxiv.org/content/10.1101/202…
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 22/07/2025
Folddisco webserver result view update: - Added description texts for AFDB - Integrated TaxoView taxonomy visualization & filter by @sunjaelee.bsky.social - Inter-residue distance clustering by DBSCAN to explore motif diversity. 🌐 search.foldseek.com/folddisco 📄 www.biorxiv.org/content/10.1...
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 22/07/2025
Today at 2 PM at 3DSIG #ISMBECCB2025, @nbordin.bsky.social presents our joint work on metagenomic-scale clustering and novel domain discovery in predicted structures! 📄 www.biorxiv.org/content/10.1... Also check out poster: B-50 lolalign Sensitive structural alignments by Lasse B-123 BFVD by Rachel
biorxiv.org
Metagenomic-scale analysis of the predicted protein structure universe
Protein structure prediction breakthroughs, notably AlphaFold2 and ESMfold, have led to an unprecedented influx of computationally derived structures. The AlphaFold Protein Structure Database now prov...
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Chan Yeong Kim @chanyeong-kim.bsky.social · 21/07/2025
Our new preprint is out! www.biorxiv.org/content/10.1... In this study, we present the largest systematic analysis of microbiome structure and function, integrating 85K uniformly processed metagenomes from diverse habitats worldwide. @podlesny.bsky.social @jonas-bio.bsky.social @borklab.bsky.social
biorxiv.org
Planetary microbiome structure and generalist-driven gene flow across disparate habitats
Microbes are ubiquitous on Earth, forming microbiomes that sustain macroscopic life and biogeochemical cycles. Microbial dispersion, driven by natural processes and human activities, interconnects mic...
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 21/07/2025
Today at 5pm, @eunbelivable.bsky.social will present her work on the Big Fantastic Viral Database (BFVD) at #ISMB2025 in BOSC. She also has a poster B-123 (tomorrow, 22nd), so please drop by to have ta chat and grab some stickers! 📄 academic.oup.com/nar/article/...
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hbkgenomics.bsky.social @hbkgenomics.bsky.social · 07/07/2025
I’m excited to share our #Folddisco preprint! 🚀 We introduce a novel pairwise-geometric feature set and an optimized index structure to enable scalable structural motif search. Dive into our case studies and key results here: www.biorxiv.org/content/10.1...
biorxiv.org
Structural motif search across the protein-universe with Folddisco
Detecting similar protein structural motifs, functionally crucial short 3D patterns, in large structure collections is computationally prohibitive. Therefore, we developed Folddisco, which overcomes this through an index of position-independent geometric features, including side-chain orientation, combined with a rarity-based scoring system. Folddisco indexes 53 million AFDB50 structures into 1.45 terabyte within 24 hours, enabling rapid detection of discontinuous or segment motifs. Folddisco is more accurate and storage-efficient than state-of-the-art methods, while being an order of magnitude faster. Folddisco is free software available at folddisco.foldseek.com and a webserver at https://search.foldseek.com/folddisco. ### Competing Interest Statement M.S. acknowledges outside interest in Stylus Medicine. The remaining authors declare no competing interests. National Research Foundation of Korea, https://ror.org/013aysd81, 2020M3A9G7103933, RS-2021-NR061659, RS-2021-NR056571, RS-2024-00396026, RS-2023-00250470 Novo Nordisk Foundation, https://ror.org/04txyc737, NNF24SA0092560
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 07/07/2025
Folddisco accurately detects discontinuous motifs like zinc fingers and segment-based motifs, previously requiring separate tools. Additionally, we built a SCOPe benchmark by sampling conserved residues from families and measuring the recall up to the first false positive. 3/9
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 07/07/2025
Folddisco builds indexes faster and smaller than previous tools: indexing AFDB50 (53M structures) takes only ~24h vs. ~20 days (extrapolated) for pyScoMotif. Querying a zinc-finger motif across AFDB50 takes just ~13s, up to 48x faster than pyScoMotif. 4/9
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 07/07/2025
Folddisco can annotate proteins: querying a canonical zinc-finger uncovers an uncharacterized oyster protein and metagenomic proteins. It also detects partial catalytic metal sites in E. coli peptide deformylase. All of these hits would be missed by Foldseek or sequence aligners. 5/9
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 07/07/2025
Folddisco can distinguish functional states. We searched GPCR activation motifs (CWxP, NPxxY, DRY), clearly separating active/inactive states. A search in the AFDB shows ~53% active, closely mirroring experimental PDB 54%, suggesting AlphaFold might follow its training conformation distribution. 6/9
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 07/07/2025
Folddisco can be applied for PPI interface searches. When querying an interface between antibody chains (gray/black), it successfully identifies matching interfaces within monomeric antibody fragments (cyan), showcasing its potential to detect novel interaction partners and interfaces. 7/9
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 07/07/2025
We provide a user-friendly Folddisco webserver, enabling instant structural motif searches in PDB, AFDB-Proteomes, AFDB50 (available later today), and ESMatlas (ESM30). Explore it here: search.foldseek.com/folddisco 8/9
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bioRxiv Bioinfo @biorxiv-bioinfo.bsky.social · 07/07/2025
Structural motif search across the protein-universe with Folddisco www.biorxiv.org/content/10.1101/202…
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 15/05/2025
We've updated our AFESM website to now include biome filtering, allowing exploration of protein structures adapted to specific environments. 🌐 afesm.foldseek.com Read more about the work in the skeetorial 🦋 bsky.app/profile/mart... or our preprint 📄 www.biorxiv.org/content/10.1...
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 27/04/2025
We identified 11,941 novel multi-domain combinations. We found membrane-associated domains (e.g., TonB dependent receptor, highlighting domain recombination rather than new folds as a driver of structural innovation. 5/n
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 27/04/2025
ESMatlas uses MGnify environmental labels. Leveraging this, we computed the lowest common biomes per structural cluster, revealing protein adaptations unique to specific environments, especially extreme ones like hyperthermal, hypersaline, and glaciers. 3/n
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 27/04/2025
AFESM: a metagenomic guide through the protein structure universe! We clustered 821M structures (AFDB&ESMatlas) into 5.12M groups; revealing biome-specific groups, only 1 new fold even after AlphaFold2 re-prediction & many novel domain combos. 🧵 🌐 afesm.foldseek.com 📄 www.biorxiv.org/content/10.1...
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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 27/04/2025
It's a big collaborative effort by @jingiyeo.bsky.social @yewonhan.bsky.social @nbordin.bsky.social, Andy Lau, Shaun M. Kandathil, @hbkgenomics.bsky.social, Eli Levy Karin, @milot.bsky.social David T. Jones and Christine Orengo. Visit our #RECOMB2025 poster (719) & talk (1 pm at B145 on April 29).
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hbkgenomics.bsky.social @hbkgenomics.bsky.social · 25/04/2025
Check out Folddisco poster at #RECOMB2025!
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snuchem.bsky.social @snuchem.bsky.social · 08/01/2025
SNU Profs Woon Ju Song & Martin Steinegger (Biology) developed the AI-based SeekRank algorithm to discover enzymes for cancer immunotherapy. doi.org/10.1093/nar/...
doi.org
Discovery of highly active kynureninases for cancer immunotherapy through protein language model
Abstract. Tailor-made enzymes empower a wide range of versatile applications, although searching for the desirable enzymes often requires high throughput s
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