Author

Thinh N. Tran

Memorial Sloan Kettering Cancer Center

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Genomics· 1

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Approach:benchmark study· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Chenlian FuiD· 1 shared January Choy· 1 shared Jennifer YuiD· 1 shared Justin JeeiD· 1 shared Leah Morales· 1 shared Madison DarmofaliD· 1 shared Michael F. BergeriD· 1 shared Michele WatersiD· 1 shared

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2026-2026 · peak 1/yr

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1 shared paperGenomics

Chenlian FuORCID

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1 paper

Recent·Most cited

Generalist large language models complement tailor-made predictors for tumor genomics interpretation

Jennifer Yu, Madison Darmofal, Michele Waters, January Choy, Thinh N. Tran, Chenlian Fu, Leah Morales, U Kaicheng, Ross L. Levine, Nikolaus Schultz, Michael F. Berger, Quaid Morris, Justin Jee

This paper evaluates generalist large language models (LLMs) in tumor genomic interpretation tasks, finding they can complement or outperform task-specific models in some cases.

bioRxiv · May 22, 2026 · PreprintGenomics