Anthony Gitter
Computational biologist; Associate Prof. at University of Wisconsin-Madison; Jeanne M. Rowe Chair at Morgridge Institute
- Reposted by Anthony GitterCan proteins fold and function with half of the amino acid alphabet? Using only 10 residues, we designed stable, mutation-resilient structures—no aromatics or basics involved. A minimalist foundation for ancient biology and synthetic design. tinyurl.com/37t8br4v #ProteinDesign #OriginsOfLife
- Reposted by Anthony GitterMy 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
- Reposted by Anthony GitterI'm really excited to break up the holiday relaxation time with a new preprint that benchmarks AlphaFold3 (AF3)/“co-folding” methods with 2 new stringent performance tests. Thread below - but first some links: A longer take: fraserlab.com/2025/12/29/k... Preprint: www.biorxiv.org/content/10.6...
- Reposted by Anthony GitterNew preprint🚨 Imagine (re)designing a protein via inverse folding. AF2 predicts the designed sequence to a structure with pLDDT 94 & you get 1.8 Å RMSD to the input. Perfect design? What if I told u that the structure has 4 solvent-exposed Trp and 3 Pro where a Gly should be? Why to be wary🧵👇
- Reposted by Anthony GitterExcited for our new paper on a genome language model for viruses in @natcomms.nature.com: "Protein Set Transformer: a protein-based genome language model to power high-diversity viromics"! Led by PhD student Cody Martin in collaboration with @anthonygitter.bsky.social doi.org/10.1038/s414...
- What are good places to post an unsolicited manuscript peer review these days? I don't have a blog. I read manuscripts across arXiv, bioRxiv, ChemRxiv, OpenReview, random white papers, journals, etc. Do I dump it on Zenodo, post it here, and send it to the authors?
- Our Assay2Mol manuscript was published at EMNLP 2025 doi.org/10.18653/v1/... See the preprint thread below for a summary of the methodology, results, and code. We added more control experiments in this version related to protein sequence identity and generated molecule size.
- @hkws.bsky.social and I are creating the Madison AI for Proteins (MAIP) group to discuss early-stage research at monthly meetups, share computational resources, and grow this local community. Visit mad-ai-proteins.github.io to sign up for announcements and watch for our 2026 events.
- Reposted by Anthony GitterThis looks like a fantastic resource to study human kinase signalling. So much MS instrument time.
- Chemical proteomics decrypts the kinases that shape the dynamic human phosphoproteome biorxiv.org/content/10.1101/202…
- Something fun and sciencey is coming soon to Madison
- The journal version of our Multi-omic Pathway Analysis of Cells (MPAC) software is now out: doi.org/10.1093/bioi... MPAC uses biological pathway graphs to model DNA copy number and gene expression changes and infer activity states of all pathway members.
- MPAC uses PARADIGM as the probabilistic model but makes many improvements: - data-driven omic data discretization - permutation testing to eliminate spurious predictions - full workflow and downstream analyses in an R package - Shiny app for interactive visualization
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- The journal version of "Biophysics-based protein language models for protein engineering" with @philromero.bsky.social is live! Mutational Effect Transfer Learning (METL) is a protein language model trained on biophysical simulations that we use for protein engineering. 1/ doi.org/10.1038/s415...
- Most protein language models train on natural protein sequence data and use the underlying evolutionary signals to score sequence variants. Instead, METL trains on @rosettacommons.bsky.social data, learning from simulated biophyiscal attributes of the sequence variants we select. 2/
- The journal version of our paper 'Chemical Language Model Linker: Blending Text and Molecules with Modular Adapters' is out doi.org/10.1021/acs.... ChemLML is a method for text-based conditional molecule generation that uses pretrained text models like SciBERT, Galactica, or T5.
- Reposted by Anthony Gitter🚨New paper 🚨 Can protein language models help us fight viral outbreaks? Not yet. Here’s why 🧵👇 1/12
- Our preprint Assay2Mol introduces uses PubChem chemical screening data as context when generating molecules with large language models. It uses assay descriptions and protocols to find relevant assays and that text plus active/inactive molecules as context for generation. 1/
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- Reposted by Anthony GitterHappy to share this interview with Weijie Zhao from NSR at #OxfordUniversityPress. It covers questions I’m often asked—why I chose Korea, AlphaFold2, my unconventional journey into academia, and research insights. Thanks again for the fun conversation. 📄 academic.oup.com/nsr/article/...
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