Author

Heng Ji

University of Illinois Urbana-ChampaignORCID 0000-0002-0464-7966Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:proteomics· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Aakanksha NaikiD· 1 shared Carl Edwards· 1 shared Martin D. BurkeiD· 1 shared Tom HopeiD· 1 shared Tushar Khot· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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1 shared paperBioinformatics

Aakanksha NaikORCID

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1 paper

Recent·Most cited

SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design

Carl Edwards, Aakanksha Naik, Tushar Khot, Martin D. Burke, Heng Ji, Tom Hope

This paper introduces SynerGPT, a model that uses in-context learning to predict drug synergy and design personalized cancer treatments based on patient biopsy data.

bioRxiv · Jul 6, 2023 · PreprintBioinformatics