Jean Fan

24.6k total citations · 4 hit papers
73 papers, 7.0k citations indexed

About

Jean Fan is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Jean Fan has authored 73 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Molecular Biology, 27 papers in Pulmonary and Respiratory Medicine and 27 papers in Oncology. Recurrent topics in Jean Fan's work include Single-cell and spatial transcriptomics (24 papers), Lung Cancer Treatments and Mutations (22 papers) and Colorectal Cancer Treatments and Studies (9 papers). Jean Fan is often cited by papers focused on Single-cell and spatial transcriptomics (24 papers), Lung Cancer Treatments and Mutations (22 papers) and Colorectal Cancer Treatments and Studies (9 papers). Jean Fan collaborates with scholars based in United States, China and South Korea. Jean Fan's co-authors include Fan Zhang, Kamil Slowikowski, Nghia Millard, Ilya Korsunsky, Yuriy Baglaenko, Po‐Ru Loh, Kevin Wei, Soumya Raychaudhuri, Michael B. Brenner and Xiaowei Zhuang and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Jean Fan

62 papers receiving 6.9k citations

Hit Papers

Fast, sensitive and accurate integration of single-cell d... 2017 2026 2020 2023 2019 2017 2019 2017 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jean Fan United States 19 4.7k 1.7k 1.3k 1.2k 947 73 7.0k
Sara Aibar Belgium 14 4.3k 0.9× 1.8k 1.1× 1.3k 1.0× 1.2k 1.0× 592 0.6× 17 6.1k
Gert Hulselmans Belgium 22 4.4k 0.9× 1.7k 1.0× 1.0k 0.8× 1.0k 0.9× 458 0.5× 30 6.3k
Shuqiang Li United States 21 4.4k 0.9× 1.5k 0.9× 852 0.7× 1.4k 1.2× 431 0.5× 44 6.1k
Timm Schroeder Switzerland 54 5.8k 1.2× 2.0k 1.2× 1.0k 0.8× 945 0.8× 409 0.4× 166 9.9k
Suoqin Jin China 17 3.0k 0.6× 1.8k 1.1× 1.0k 0.8× 769 0.6× 696 0.7× 34 5.4k
Kevin Wei United States 14 3.2k 0.7× 2.0k 1.2× 1.1k 0.8× 857 0.7× 486 0.5× 23 5.6k
Andrew J. Hill United States 11 4.7k 1.0× 1.2k 0.7× 827 0.6× 1.7k 1.4× 487 0.5× 13 6.3k
Kamil Slowikowski United States 12 3.1k 0.7× 1.7k 1.0× 763 0.6× 771 0.6× 445 0.5× 17 5.0k
Manu Setty United States 21 3.2k 0.7× 2.7k 1.6× 1.7k 1.3× 1.1k 0.9× 417 0.4× 31 6.0k
Hannah A. Pliner United States 13 5.1k 1.1× 1.3k 0.8× 671 0.5× 1.2k 1.0× 362 0.4× 14 6.3k

Countries citing papers authored by Jean Fan

Since Specialization
Citations

This map shows the geographic impact of Jean Fan'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 Jean Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean Fan more than expected).

Fields of papers citing papers by Jean Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean Fan. 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 Jean Fan. The network helps show where Jean Fan may publish in the future.

Co-authorship network of co-authors of Jean Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Jean Fan. A scholar is included among the top collaborators of Jean Fan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jean Fan. Jean Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Macaluso, Nicolas C., Yukang Li, Bartholomew Starich, et al.. (2025). Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts. Science Advances. 11(17). eads1875–eads1875. 3 indexed citations
2.
Qi, Ziyuan, et al.. (2025). Integrated Transcriptomic and Epigenomic Analysis Reveals Mechanisms Underlying Melanotic Spot Formation in Red Tilapia (Oreochromis spp.). International Journal of Molecular Sciences. 26(9). 4370–4370.
3.
Brusko, Maigan A., Lyla Atta, Mark A. Atkinson, et al.. (2025). Characterizing cell-type spatial relationships across length scales in spatially resolved omics data. Nature Communications. 16(1). 350–350. 1 indexed citations
4.
Fan, Jean. (2025). Revisiting the somatic mutation theory of cancer pathogenesis. Nature Reviews Genetics. 27(2). 116–116.
5.
Atta, Lyla, et al.. (2024). SEraster: a rasterization preprocessing framework for scalable spatial omics data analysis. Bioinformatics. 40(7). 3 indexed citations
6.
Subudhi, Sumit K., Chih‐Yi Liao, Shun Zhang, et al.. (2024). The efficacy and safety of tinengotinib in patients with heavily pretreated metastatic castration-resistant prostate cancer (mCRPC).. Journal of Clinical Oncology. 42(4_suppl). 133–133.
7.
Trouvé, Alain, Laurent Younès, Michael Kunst, et al.. (2024). Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections. Nature Communications. 15(1). 3530–3530. 3 indexed citations
8.
Zhang, Panpan, Jifang Gong, Zuoxing Niu, et al.. (2024). Tinengotinib (TT-00420) in combination with atezolizumab in Chinese patients (pts) with biliary tract carcinoma (BTC): Preliminary efficacy and safety results from a phase Ib/II study.. Journal of Clinical Oncology. 42(3_suppl). 473–473. 1 indexed citations
9.
Fan, Jean. (2023). Why it’s worth making computational methods easy to use. Nature. 1 indexed citations
10.
Miller, Brendan, Feiyang Huang, Lyla Atta, Arpan Sahoo, & Jean Fan. (2022). Reference-free cell type deconvolution of multi-cellular pixel-resolution spatially resolved transcriptomics data. Nature Communications. 13(1). 2339–2339. 104 indexed citations
11.
Atta, Lyla, Arpan Sahoo, & Jean Fan. (2021). VeloViz: RNA velocity-informed embeddings for visualizing cellular trajectories. Bioinformatics. 38(2). 391–396. 10 indexed citations
12.
Miller, Brendan, Dhananjay Bambah-Mukku, Catherine Dulac, Xiaowei Zhuang, & Jean Fan. (2021). Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities. Genome Research. 31(10). 1843–1855. 81 indexed citations
13.
Fan, Jean, Kamil Slowikowski, & Fan Zhang. (2020). Single-cell transcriptomics in cancer: computational challenges and opportunities. Experimental & Molecular Medicine. 52(9). 1452–1465. 122 indexed citations
14.
Korsunsky, Ilya, Nghia Millard, Jean Fan, et al.. (2019). Fast, sensitive and accurate integration of single-cell data with Harmony. Nature Methods. 16(12). 1289–1296. 4105 indexed citations breakdown →
15.
Fan, Jean. (2019). Differential Pathway Analysis. Methods in molecular biology. 1935. 97–114. 2 indexed citations
16.
Lake, Blue B., Song Chen, Brandon C. Sos, et al.. (2017). Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain. Nature Biotechnology. 36(1). 70–80. 569 indexed citations breakdown →
17.
Schüler, Martin, Luis Paz‐Ares, Lecia V. Sequist, et al.. (2017). First-line afatinib for advanced EGFRm+ NSCLC: Analysis of long-term responders (LTRs) in the LUX-Lung (LL) 3, 6 and 7 trials. Annals of Oncology. 28. ii33–ii33. 2 indexed citations
20.
Zhang, Xiaochang, Ming Hui Chen, Xuebing Wu, et al.. (2016). Cell-Type-Specific Alternative Splicing Governs Cell Fate in the Developing Cerebral Cortex. Cell. 166(5). 1147–1162.e15. 231 indexed citations

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.

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