Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis
Most Cited Paper
in Cancer Genomics and Diagnostics
18 Months Post-Publication
Class of 2026
“Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis”
A research intelligence initiative by Pepkio
pri.pepkio.com/top-papers/cancer-genomics-and-diagnostics/2026/
Topics
GPT-4 · large language model · Cell type annotation · Single-cell RNA sequencing · marker genes · manual annotation · Concordance evaluation · automated annotation · GPTCelltype · R software · tissue types · Single-cell RNA sequencing
Share
Cite this ranking
Pepkio Research Index (PRI). Topics and Trends in Most Cited Cancer Genomics and Diagnostics Papers, Class of 2026. https://pri.pepkio.com/top-papers/cancer-genomics-and-diagnostics/2026. Accessed 2026-07-13. Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459