Author

Han Si

Genmab (United States)ORCID 0000-0001-5655-3374Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Assay:clinical cohort / trial· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Assay:imaging· 1

Frequent Co-Authors

Brandon W. HiggsiD· 2 shared Anantharaman MuthuswamyiD· 1 shared Arshad AhmadiD· 1 shared Deepti R. NagarkariD· 1 shared Eda Zhou· 1 shared Jenny Kaufmann· 1 shared Karen Stephansen· 1 shared Maximilian Farma· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Brandon W. HiggsORCID

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2 papers

Recent·Most cited

BioinformaticsComputational and Structural Biotechnology JournalPeer-reviewedMar 1, 2026

Comparative Analysis of Pathology Foundation Models for Automated Detection of Tertiary Lymphoid Structures in H&E-Stained Digital Pathology Images

Meijian Guan, Yu Sun, Merzu Kebede Belete…·Han Si

This study evaluates pathology foundation models for detecting tertiary lymphoid structures in cancer tissues, finding strong performance in PDAC but challenges in HNSCC due to tumor heterogeneity.

1 citation

humanimaging

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Cancer BiologyCurrent OncologyPeer-reviewedSep 30, 2025

Mechanistically explainable AI model for predicting synergistic cancer therapy combinations

Han Si, Sanyam Kumar, Sneh Lata…·Brandon W. Higgs

This paper introduces an LLM-based framework that predicts synergistic cancer drug combinations using drug data and a knowledge graph, achieving an F1 score of 0.80.

3 citations

humanclinical cohort / trial

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