Jiecong Lin @JasonLinjc
Postdoc at @harvardmed @MGHPathology @DFBC_PedCare @HKUniversity, passionate about developing deep learning models to decipher gene regulation sites.google.com/view/jieconglin Joined July 2017-
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This is the single most important resource for genomics research. Earth’s DNA is now at our fingertips. What a heroic effort and mega congrats to @RayanChikhi and @RNA_Life!!!
This is the single most important resource for genomics research. Earth’s DNA is now at our fingertips. What a heroic effort and mega congrats to @RayanChikhi and @RNA_Life!!!
In the genomics community, we have focused pretty heavily on achieving state-of-the-art predictive performance. While undoubtedly important, how we *use* these models after training is potentially even more important. tangermeme v1.0.0 is out now. Hope you find it useful!
In April '25, I shared the origin story of Evo on the TED stage. I talked about the motivation behind generating DNA with AI and how it could change what’s possible. It was an incredible experience. full video: go.ted.com/ericnguyen
🚀 OncoGAN is now published in @CellGenomics! We introduce an AI system that generates high-fidelity, privacy-preserving synthetic cancer genomes — now open-access. 🔍 Why OncoGAN? --No patient data leakage — critical for genomic privacy --Built-in ground truth — ideal for…
Tonight’s reading material. A team at DeepMind wrote this piece on how you must think about GPUs. Essential for AI engineers and researchers.
🚀 Introducing PantheonOS (pantheonOS.stanford.edu): A Fully Open-Source Agent OS for Science PantheonOS began as a research project in my Stanford lab and has since evolved into a vision to redefine data science in the era of AI—starting with computational biology, especially…
I'm glad that I had a chance to contribute to this wide-ranging article discussing the myriad ways ML is being used in genomics: nature.com/articles/d4158…
Introducing STELLA — a Self-Evolving LLM agent that autonomously creates its own tools to navigate and accelerate biomedical research. 🤖 Why It Matters: ⛓️ The Limitation: Most AI agents are fundamentally limited by a fixed set of predefined tools. This is a major bottleneck…
🤝Excited to partner with Tamarind @kavi_deniz to build towards an agentic AI protein designer. 🔁 Agentic protein optimization — Starting from a sequence, Biomni iteratively improves thermostability by orchestrating AlphaFold-2, ThermoMPNN, and reasoning over predictions and…
Excited to be at #ISMBECCB2025! I'll be presenting at RegSys on "Learning the Regulatory Genome by Destruction and Creation" (Thursday 3:15PM in Room 11BC). I'm looking forward to connecting with both new and old friends throughout the conference! 🧬 #CRISPR #Genomics #Diffusion
Some aspects of AI discourse seem to come from a different planet, oblivious to basic realities on Earth. AI for science is one such area. In this new essay, @sayashk and I argue that visions of accelerating science through AI should be considered unserious if they don't confront…
📢New conference where AI is the primary author and reviewer! agents4science.stanford.edu Current venues don't allow AI-written papers, so it's hard to assess the +/- of such works🤔 #Agents4Science solicits papers where AI is the main author w/ human advisors. 💡Initial reviews by…
🧬 Excited to open-source Biomni! With just a few lines of code, you can now automate biomedical research with AI agent! We are releasing Biomni A1 (agent) + E1 (env) with 150 specialized tools, 59 databases, and 105 software. E1 is our first attempt at curating the bio-agent…
🤝Excited to announce @ProjectBiomni × @AnthropicAI! AI agents are set to transform how biologists do everyday research. Thanks to this partnership, the platform is now free for scientists worldwide: biomni.stanford.edu Learn more: anthropic.com/customers/biom…
New OpenProblems paper out! 📝 Led by Malte Lücken with Smita Krishnaswamy, we present openproblems.bio – a community-driven platform benchmarking single-cell analysis methods. Excited about transparent, evolving best practices for the field! 🔗 nature.com/articles/s4158…
Genomic Touchstone: Benchmarking Genomic Language Models in the Context of the Central Dogma biorxiv.org/content/10.110…
Today marks the end of en-JUNE-eering, the month where I focused mostly on the nitty gritty of improving genomics ML infrastructure. Here are some of the highlights:
Delighted to announce @arcinstitute's Virtual Cell Challenge - a recurring, open, community-driven challenge to benchmark cellular foundation models See our announcement in @CellCellPress below, with prizes up to $100,000, sponsored by @nvidia @10xGenomics @UltimaGenomics!
Delighted to announce @arcinstitute's Virtual Cell Challenge - a recurring, open, community-driven challenge to benchmark cellular foundation models See our announcement in @CellCellPress below, with prizes up to $100,000, sponsored by @nvidia @10xGenomics @UltimaGenomics! https://t.co/9fITNQBlE8
This a really exciting leap forward for genomic sequence to activity gene regulation models. It is a genuine improvement over pretty much all SOTA models spanning a wide range of regulatory, transcriptional and post-transcriptional processes. 1/
This a really exciting leap forward for genomic sequence to activity gene regulation models. It is a genuine improvement over pretty much all SOTA models spanning a wide range of regulatory, transcriptional and post-transcriptional processes. 1/

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