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Ada Fang

As seen in: BioRxiv, Preprints.org

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Ada Fang’s Journalist Portfolio

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Articles

Closing the Loop in AI-Driven Biomedical Discovery

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By Ada Fang, Kevin H Li, Ayush Noori
| Preprints.org
You are already at the latest version AI scientists generate hypotheses, propose experiments, and analyze datasets, and several have produced findings that were confirmed in the laboratory. Although they are opening a path to autonomous discovery, the loop from hypothesis to experiment to revised hypothesis is still often anecdotal. Here, we consider how that loop could be closed to enable AI-driven biomedical discovery.
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Computer Science > Artificial Intelligence

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By Yasha Ektefaie, Ada Fang, Sham M. Kakade
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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ATOMICA: Learning Universal Representations of Intermolecular Interactions

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By Ada Fang, Zaixi Zhang, Andrew Zhou, Marinka Zitnik
| BioRxiv
Abstract Molecular interactions underlie nearly all biological processes, but most machine learning models treat molecules in isolation or specialize in a single type of interaction, such as protein-ligand or protein-protein binding. This siloed approach prevents generalization across biomolecular classes and limits the ability to model interaction interfaces systematically.
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