Tu Tran

442 citations
9 papers · 317 · 1 hit paper · h-index 6

Impact in

Papers in

    • Single-cell and spatial transcriptomics 2
    • Gene expression and cancer classification 1
    • Vascular Tumors and Angiosarcomas 1

Tu Tran

8 papers receiving 305 citations

Tu Tran's Hit Papers

A visual–omics foundation model to bridge histopathology with spatial transcriptomics 2025 · 25 citations
250Years since publication510152025

Peers

Tu Tran
Comparison fields: 5 of 37
  • Pathology and Forensic Medicine 134
  • Radiation 50
  • Radiology, Nuclear Medicine and Imaging 67
  • Neurology 32
  • Cancer Research 28
Replace Georgios Ntentas with:
Georgios Ntentas United Kingdom
Cristina Piva Italy
Bart Meulemans Belgium
Andrea Stevens United Kingdom
N. Lessard France
C. Pichenot France
T. Messaï France
Eric Yi-Liang Shen Taiwan
Patrick Melchior Germany
Alice Mège France
Tu Tran relative to Georgios Ntentas United Kingdom Georgios Ntentas's profile →
Citations per field
00.5×10×15×
Georgios Ntentas · 1×
Citations per year

Countries citing papers authored by Tu Tran

Since Specialization
Citations

This map shows the geographic impact of Tu Tran's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tu Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tu Tran more than expected).

Fields of papers citing papers by Tu Tran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tu Tran. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tu Tran. The network helps show where Tu Tran may publish in the future.

Co-authors

The 25 scholars most cited alongside Tu Tran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tu Tran Line = papers co-authored together Tu Tran links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2007122
2 2007106
3 200650
4
A visual–omics foundation model to bridge histopathology with spatial transcriptomics
Hit paper breakdown →
202525
5 20117
6 20255
7 20231
8 20221
9 20250

About Tu Tran

Tu Tran is a scholar working on Molecular Biology, Oncology, Biophysics, Surgery and Pathology and Forensic Medicine, having authored 9 papers that have together received 317 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (2 papers), Single-cell and spatial transcriptomics (2 papers), Brain Metastases and Treatment (1 paper), Vascular Tumors and Angiosarcomas (1 paper), Breast Cancer Treatment Studies (1 paper), Meningioma and schwannoma management (1 paper), Gene expression and cancer classification (1 paper) and Breast Implant and Reconstruction (1 paper). The work is most often cited by research in Pathology and Forensic Medicine (134 citations), Radiation (50 citations), Radiology, Nuclear Medicine and Imaging (67 citations), Neurology (32 citations) and Cancer Research (28 citations). Tu Tran has collaborated with scholars based in United States and Canada. Frequent co-authors include David Hodgson, Eng‐Siew Koh, Melania Pintilie, Richard Tsang, David J. Brenner, Tony Xu, Rainer K. Sachs, M. Heydarian, June Key Chung and Narinder Paul. Their work appears in journals such as The American Surgeon, Journal of Surgical Oncology, Nature Methods, Radiation Oncology and Journal of Surgical Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact