🧬 Another super exciting new work from the lab: Decoding the gene regulatory landscape through multimodal learning of protein–DNA interactions. 👉 Link to preprint: biorxiv.org/content/10.1101/… In this work, we introduce Chromnitron, a biologically grounded multimodal foundation model that decodes the global gene regulatory landscape by hundreds to thousands of proteins binding in the genome. ⁉️ Why is this protein-centered view of regulatory genomics so important? DNA sequence 🧬provides the same genetic blueprint, but the regulatory logic that gives rise to diverse cell types and states – in both health and disease conditions – is executed by the 100s-1000s of chromatin proteins that differentially read the DNA sequences to establish cell-type-specific gene expression programs. 🤖 Chromnitron is specifically developed to decode this cell-type-specific regulatory logic. Designed to learn from the first principles that determines protein–DNA interactions in the cell, Chromnitron integrates 1) genomic DNA sequence, 2) cell-type-specific chromatin states, and importantly, 3) protein sequence-encoded structural features. 👨🏻‍💻 Through large-scale pre-training & fine-tuning with a finely curated atlas of high-quality datasets, Chromnitron learns the shared and protein-specific mechanisms of protein–DNA interactions, and thus can accurately predict the binding landscapes across hundreds of proteins in unseen cell types. 💡Chromnitron isn’t just accurate and cell-type-specific prediction — it is a discovery engine! With Chromnitron: we identified novel regulators of T cell exhaustion (ZNF865 & ZNF766); we reconstructed the dynamic regulatory landscapes of how global chromatin proteins orchestrate neurodevelopment. 🔮 Chromnitron represents a significant step toward predictive, interpretable, and mechanistic understanding of gene regulation and cell fate determination. We expect Chromnitron to accelerate discovery and engineering in regulatory genomics, particularly in human biology, and empower therapeutic opportunities. 🙏🏻 Last, this is another wonderful collaboration with Dr. Aristotelis Tsirigos @artsinyc, and led by the brilliant Drs. Jimin Tan @tan_jimin, Xi Fu @alexanderfuxi, and Xinyu Ling @Dennislxy, and many more co-authors and friends who helped make this work truly possible! 👉 Find out more about the model and discoveries (e.g. architecture, interpretability, benchmarking, generalizability, etc): biorxiv.org/content/10.1101/… #MultimodalAI #GeneRegulation #TranscriptionFactor #RegulatoryGenomics #CellFate #AIinBiology