Jiangchun Xu

6.3k total citations
27 papers, 2.3k citations indexed

About

Jiangchun Xu is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Jiangchun Xu has authored 27 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 9 papers in Cancer Research and 5 papers in Oncology. Recurrent topics in Jiangchun Xu's work include Epigenetics and DNA Methylation (6 papers), Cancer, Lipids, and Metabolism (6 papers) and Molecular Biology Techniques and Applications (5 papers). Jiangchun Xu is often cited by papers focused on Epigenetics and DNA Methylation (6 papers), Cancer, Lipids, and Metabolism (6 papers) and Molecular Biology Techniques and Applications (5 papers). Jiangchun Xu collaborates with scholars based in United States, South Korea and Brazil. Jiangchun Xu's co-authors include Bruce A. Woda, Gary R. Fanger, Zhong Jiang, Steven G. Reed, Raymond L. Houghton, Steven G. Reed, Roberto Badaró, Xinqun Zhang, John A. Stolk and Karen Dresser and has published in prestigious journals such as The Journal of Experimental Medicine, Blood and The Journal of Immunology.

In The Last Decade

Jiangchun Xu

26 papers receiving 2.2k citations

Peers

Jiangchun Xu

PRM

ONCOL

IMMUN

Mona El‐Bahrawy United Kingdom

Lisa Simi Italy

Ruth Birbe United States

Caigang Liu China

Jurga Sauvageot United States

Murry W. Wynes United States

William B. Isaacs United States

Turid Knutsen United States

Diane L. Persons United States

Zhao-You Tang China

Mona El‐Bahrawy United Kingdom

Jiangchun Xu

1.4k ×1.2

412 ×0.5

PRM

627 ×1.0

630 ×1.5

ONCOL

274 ×1.1

IMMUN

Citations per year, relative to Jiangchun Xu Jiangchun Xu (= 1×) peers Mona El‐Bahrawy

Countries citing papers authored by Jiangchun Xu

Since Specialization

Citations

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

Fields of papers citing papers by Jiangchun Xu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiangchun Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Jiangchun Xu. A scholar is included among the top collaborators of Jiangchun Xu 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 Jiangchun Xu. Jiangchun Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Xu, Jiangchun, et al.. (2025). Assembly and delivery of large DNA via chromosome elimination in yeast. Nature Protocols. 20(12). 3755–3782. 1 indexed citations

Nguyen, Aaron, Songmao Zheng, Guizhong Liu, et al.. (2021). ADG153, an Anti-CD47 Monoclonal Antibody Prodrug, Has Strong In Vivo Anti-Tumor Activity, Minimal RBC-Related and Antigen Sink Liabilities, and Extended Half Life in Comparison with Benchmark Clinical Antibodies of the Same IgG Subclass. Blood. 138(Supplement 1). 3342–3342. 3 indexed citations

Nie, Zhe, Lihong Shi, Chon Lai, et al.. (2018). Structure-based design and discovery of potent and selective lysine-specific demethylase 1 (LSD1) inhibitors. Bioorganic & Medicinal Chemistry Letters. 29(1). 103–106. 12 indexed citations

Bennett, Malcolm J., Yiqin Wu, Amogh Boloor, et al.. (2018). Design, synthesis and biological evaluation of novel 4-phenylisoquinolinone BET bromodomain inhibitors. Bioorganic & Medicinal Chemistry Letters. 28(10). 1811–1816. 7 indexed citations

Nie, Zhe, Lihong Shi, Chon Lai, et al.. (2018). Structure-based design and discovery of potent and selective KDM5 inhibitors. Bioorganic & Medicinal Chemistry Letters. 28(9). 1490–1494. 32 indexed citations

Metzger, Eric, Sylvia Urban, Dominica Willmann, et al.. (2017). KDM4 Inhibition Targets Breast Cancer Stem–like Cells. Cancer Research. 77(21). 5900–5912. 73 indexed citations

Lim, Ho-Yeong, Insuk Sohn, Shibing Deng, et al.. (2013). Prediction of Disease-free Survival in Hepatocellular Carcinoma by Gene Expression Profiling. Annals of Surgical Oncology. 20(12). 3747–3753. 110 indexed citations

Wang, Kai, Ho Yeong Lim, Stephanie T. Shi, et al.. (2013). Genomic Landscape of Copy Number Aberrations Enables the Identification of Oncogenic Drivers in Hepatocellular Carcinoma. Hepatology. 58(2). 706–717. 137 indexed citations

Wang, Kai, Gang Li, Zhi Xie, et al.. (2011). Liverome: a curated database of liver cancer-related gene signatures with self-contained context information. BMC Genomics. 12(S3). S3–S3. 118 indexed citations

10.

Zehentner, Barbara K., Heather Secrist, Xinqun Zhang, et al.. (2006). Detection of α-Methylacyl-Coenzyme-A Racemase Transcripts in Blood and Urine Samples of Prostate Cancer Patients. Molecular Diagnosis & Therapy. 10(6). 397–403. 23 indexed citations

11.

Stolk, John A., David A Molesh, Patricia D. McNeill, et al.. (2005). VSGP/F-Spondin: A New Ovarian Cancer Marker. Tumor Biology. 26(5). 245–257. 23 indexed citations

12.

Jiang, Z., Chin‐Lee Wu, Bruce A. Woda, et al.. (2004). Alpha‐methylacyl‐CoA racemase: a multi‐institutional study of a new prostate cancer marker. Histopathology. 45(3). 218–225. 105 indexed citations

13.

Stolk, John A., Yuqiu Jiang, Craig H. Day, et al.. (2004). P704P, P712P, and P775P: A genomic cluster of prostate‐specific genes. The Prostate. 60(3). 214–226. 2 indexed citations

14.

Jiang, Zhong, Gary R. Fanger, Bruce A. Woda, et al.. (2003). Expression of α-methylacyl-coa racemase (p504s) in various malignant neoplasms and normal tissues: a study of 761 cases. Human Pathology. 34(8). 792–796. 144 indexed citations

15.

Jiang, Zhong, Gary R. Fanger, Barbara F. Banner, et al.. (2003). A dietary enzyme: α-methylacyl-CoA racemase/P504S is overexpressed in colon carcinoma. Cancer Detection and Prevention. 27(6). 422–426. 69 indexed citations

16.

Jiang, Zhong, Chin‐Lee Wu, Bruce A. Woda, et al.. (2002). P504S/α-Methylacyl-CoA Racemase. The American Journal of Surgical Pathology. 26(9). 1169–1174. 132 indexed citations

17.

Jiang, Yuqiu, Susan L. Harlocker, David A Molesh, et al.. (2002). Discovery of differentially expressed genes in human breast cancer using subtracted cDNA libraries and cDNA microarrays. Oncogene. 21(14). 2270–2282. 66 indexed citations

18.

Houghton, Raymond L., Davin C. Dillon, David A Molesh, et al.. (2001). Transcriptional Complementarity in Breast Cancer: Application to Detection of Circulating Tumor Cells. Molecular Diagnosis. 6(2). 79–91. 44 indexed citations

19.

Jiang, Zhong, Bruce A. Woda, Kenneth L. Rock, et al.. (2001). P504S. The American Journal of Surgical Pathology. 25(11). 1397–1404. 295 indexed citations

20.

Villaret, Douglas B., Tongtong Wang, Davin C. Dillon, et al.. (2000). Identification of Genes Overexpressed in Head and Neck Squamous Cell Carcinoma Using a Combination of Complementary DNA Subtraction and Microarray Analysis. The Laryngoscope. 110(3). 374–381. 160 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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