Cong Yan

4.0k total citations · 1 hit paper
69 papers, 3.2k citations indexed

About

Cong Yan is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Cong Yan has authored 69 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Immunology, 32 papers in Molecular Biology and 18 papers in Oncology. Recurrent topics in Cong Yan's work include Immune cells in cancer (22 papers), Immune Cell Function and Interaction (15 papers) and Sphingolipid Metabolism and Signaling (11 papers). Cong Yan is often cited by papers focused on Immune cells in cancer (22 papers), Immune Cell Function and Interaction (15 papers) and Sphingolipid Metabolism and Signaling (11 papers). Cong Yan collaborates with scholars based in United States, China and Poland. Cong Yan's co-authors include Hong Du, Jeffrey A. Whitsett, Peng Qu, Ting Zhao, Lingyan Wu, Erika L. Pearce, David O’Sullivan, Wandy L. Beatty, Nada A. Abumrad and Christina M. O’Neill and has published in prestigious journals such as Journal of Biological Chemistry, Blood and Immunity.

In The Last Decade

Cong Yan

62 papers receiving 3.2k citations

Hit Papers

Cell-intrinsic lysosomal lipolysis is essential for alter... 2014 2026 2018 2022 2014 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Cell-intrinsic lysosomal lipolysis is essential for alternative activation of macrophages
    2014 897 citations Cong Yan, Hong Du et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cong Yan United States 30 1.6k 1.4k 649 538 502 69 3.2k
Gabrielle Paulsson‐Berne Sweden 32 1.2k 0.8× 1.2k 0.8× 283 0.4× 329 0.6× 442 0.9× 57 3.0k
Hong Du United States 38 1.8k 1.1× 1.9k 1.4× 712 1.1× 369 0.7× 609 1.2× 104 4.4k
Gianna Baroni Italy 31 752 0.5× 996 0.7× 1.3k 1.9× 353 0.7× 458 0.9× 81 3.0k
Christopher L. Jackson United Kingdom 29 1.0k 0.7× 1.1k 0.8× 357 0.6× 423 0.8× 1.0k 2.0× 57 3.4k
David R. Soto‐Pantoja United States 28 862 0.6× 1.0k 0.7× 494 0.8× 177 0.3× 289 0.6× 58 2.3k
Clément Cochain Germany 29 1.9k 1.2× 1.5k 1.1× 324 0.5× 192 0.4× 380 0.8× 42 3.4k
Yoko Kojima Japan 23 1.1k 0.7× 1.0k 0.7× 187 0.3× 411 0.8× 484 1.0× 51 3.1k
Ganapati H. Mahabeleshwar United States 31 998 0.6× 2.1k 1.5× 446 0.7× 210 0.4× 768 1.5× 46 3.5k
William Blanco-Bose Switzerland 17 1.3k 0.8× 2.3k 1.6× 674 1.0× 161 0.3× 376 0.7× 22 4.8k

Countries citing papers authored by Cong Yan

Since Specialization
Citations

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

Fields of papers citing papers by Cong Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cong Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Cong Yan. A scholar is included among the top collaborators of Cong Yan 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 Cong Yan. Cong Yan 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.
Luan, Xiaodong, Cong Yan, Xuelian Ren, et al.. (2025). Epigenetic regulation of cardiac tissue development by lysine lactylation. 3(2). 82–97. 2 indexed citations
2.
Zhou, Tong, Yuqing Feng, Delu Che, et al.. (2025). MRGPRX2-Mediated Mast Cell Activation Promotes Malignant Progression of Cutaneous Squamous Cell Carcinoma through IL-17A Release. Journal of Investigative Dermatology.
3.
4.
Zhao, Ting, Sheng Liu, Nasser H. Hanna, et al.. (2023). LAL deficiency induced myeloid-derived suppressor cells as targets and biomarkers for lung cancer. Journal for ImmunoTherapy of Cancer. 11(3). e006272–e006272. 6 indexed citations
5.
Zhao, Ting, Sheng Liu, Nasser H. Hanna, et al.. (2022). Lysosomal acid lipase, CSF1R, and PD-L1 determine functions of CD11c+ myeloid-derived suppressor cells. JCI Insight. 7(17). 11 indexed citations
6.
Zhao, Ting, et al.. (2020). Lysosomal Acid Lipase Deficiency Controls T- and B-Regulatory Cell Homeostasis in the Lymph Nodes of Mice with Human Cancer Xenotransplants. American Journal Of Pathology. 191(2). 353–367. 15 indexed citations
7.
Zhao, Ting, et al.. (2019). Transthyretin Stimulates Tumor Growth through Regulation of Tumor, Immune, and Endothelial Cells. PMC.
8.
Zhang, Wenjing, et al.. (2017). Rab7 GTPase controls lipid metabolic signaling in myeloid-derived suppressor cells. PMC. 1 indexed citations
9.
Eichmann, Thomas O., Ulrike Taschler, Kathrin A. Zierler, et al.. (2016). Lysosomal Acid Lipase Hydrolyzes Retinyl Ester and Affects Retinoid Turnover. Journal of Biological Chemistry. 291(34). 17977–17987. 49 indexed citations
10.
Wu, Lingyan, et al.. (2015). Establishment of lal-/- myeloid lineage cell line that resembles myeloid-derived suppressive cells. PMC.
11.
Du, Hong, et al.. (2015). Hepatocyte-Specific Expression of Human Lysosome Acid Lipase Corrects Liver Inflammation and Tumor Metastasis in lal(-/-) Mice. PMC. 1 indexed citations
12.
Wu, Lingyan, et al.. (2015). Establishment of lal-/- Myeloid Lineage Cell Line That Resembles Myeloid-Derived Suppressive Cells. PLoS ONE. 10(3). e0121001–e0121001. 9 indexed citations
13.
Zhao, Ting, et al.. (2015). Activation of mTOR pathway in myeloid-derived suppressor cells stimulates cancer cell proliferation and metastasis in lal(-/-) mice. PMC.
14.
Zhao, Ting, Hong Du, Xia Ding, Kenneth W. Walls, & Cong Yan. (2014). Activation of mTOR pathway in myeloid-derived suppressor cells stimulates cancer cell proliferation and metastasis in lal−/− mice. Oncogene. 34(15). 1938–1948. 55 indexed citations
15.
Du, Hong, et al.. (2013). Critical Role of the mTOR Pathway in Development and Function of Myeloid-Derived Suppressor Cells in lal−/− Mice. American Journal Of Pathology. 184(2). 397–408. 31 indexed citations
16.
Li, Yuan, et al.. (2011). Api6/AIM/Spα/CD5L Overexpression in Alveolar Type II Epithelial Cells Induces Spontaneous Lung Adenocarcinoma. Cancer Research. 71(16). 5488–5499. 44 indexed citations
17.
Wu, Lingyan, Hong Du, Yuan Li, Peng Qu, & Cong Yan. (2011). Signal Transducer and Activator of Transcription 3 (Stat3C) Promotes Myeloid-Derived Suppressor Cell Expansion and Immune Suppression during Lung Tumorigenesis. American Journal Of Pathology. 179(4). 2131–2141. 72 indexed citations
18.
Qu, Peng, Hong Du, Yuan Li, & Cong Yan. (2009). Myeloid-Specific Expression of Api6/AIM/Spα Induces Systemic Inflammation and Adenocarcinoma in the Lung. The Journal of Immunology. 182(3). 1648–1659. 48 indexed citations
19.
20.
Lian, Xuemei, Yulin Qin, Shaikh Abu Hossain, et al.. (2005). Overexpression of Stat3C in Pulmonary Epithelium Protects against Hyperoxic Lung Injury. The Journal of Immunology. 174(11). 7250–7256. 58 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Gabrielle Paulsson‐Berne Breakdown of academic impact, for papers by Hong Du Breakdown of academic impact, for papers by Gianna Baroni Breakdown of academic impact, for papers by Christopher L. Jackson Breakdown of academic impact, for papers by David R. Soto‐Pantoja Breakdown of academic impact, for papers by Clément Cochain Breakdown of academic impact, for papers by Yoko Kojima Breakdown of academic impact, for papers by Ganapati H. Mahabeleshwar Breakdown of academic impact, for papers by William Blanco-Bose
Rankless by CCL
2026