
Michelle M. Li (李敏蕊)
@_michellemli
Contextual learning on graphs for precision medicine | Biomedical Informatics PhD @marinkazitnik @HarvardDBMI | Math+CS BS @Stanford | Founder @rerootstem
ID: 288493709
http://michellemli.com 26-04-2011 23:26:17
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Excited to share TxGNN, a model that identifies potential therapies from existing medicines for thousands of diseases. Trained across 17,080 diseases, TxGNN predicts drug candidates for conditions with limited or no treatment options, including rare diseases Nature Medicine


Putting proteins in context: Clara (Mengzhou) Hu & Trey Ideker spotlight PINNACLE, a geometric DL approach that generates contextualized representations of proteins by combined analysis of protein interactions and multiorgan single-cell transcriptomics cell.com/cell-systems/a…

A remarkable visionary perspective for the role of #AI agents to promote discovery in life science, laid out by Marinka Zitnik and colleagues Cell cell.com/cell/fulltext/… Kempner Institute at Harvard University DBMI at Harvard Med Broad Institute







Excited to announce SPECTRA has been published in Nature Machine Intelligence! Use this link to access the paper: rdcu.be/d2D0z A big thank you to all my collaborators Andrew Shen @ ICLR 2025, Daria Bykova, and Maximillian Marin and to my advisors Marinka Zitnik and Maha Farhat.

Are biomedical AI models truly as smart as they seem? Yasha Ektefaie rdcu.be/d2D0z Our Nature Machine Intelligence paper introduces SPECTRA, a framework that evaluates models by considering the full spectrum of cross-split overlap: train-test similarity SPECTRA reveals gaps in


Medicine thrives on knowledge, yet clinical vocabularies are fragmented. AI struggles to unify this knowledge, creating a gap in precision medicine. Excited to share unified clinical vocabulary embeddings, a project led by stellar Ruthie Johnson Half of healthcare foundation AI


(1/4) Excited to introduce ProCyon: a multimodal foundation model to model, generate, and predict protein phenotypes, led by stellar Owen Queen Yepeng Robert Calef Valentina Giunchiglia 👉 biorxiv.org/content/10.110… ProCyon is an 11B parameter multimodal model that integrates protein



What if you could rewind time, tweak a decision, and watch the future unfold differently, one precise edit at a time? That’s exactly what CLEF does for sequences in biology and medicine Michelle M. Li (李敏蕊) Controllable sequence editing: generate precise, time-sensitive




📢 🧬 New preprint! Can we predict which cancer patients will benefit, before treatment begins? Wan Xiang Shen Immunotherapy saves lives but many patients don’t respond to treatment, and we still lack reliable tools to predict who will benefit We introduce COMPASS, foundation
