Aixiang Jiang

5.6k total citations · 2 hit papers
48 papers, 2.7k citations indexed

About

Aixiang Jiang is a scholar working on Oncology, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Aixiang Jiang has authored 48 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 17 papers in Molecular Biology and 16 papers in Pathology and Forensic Medicine. Recurrent topics in Aixiang Jiang's work include Lymphoma Diagnosis and Treatment (14 papers), Chronic Lymphocytic Leukemia Research (5 papers) and Angiogenesis and VEGF in Cancer (5 papers). Aixiang Jiang is often cited by papers focused on Lymphoma Diagnosis and Treatment (14 papers), Chronic Lymphocytic Leukemia Research (5 papers) and Angiogenesis and VEGF in Cancer (5 papers). Aixiang Jiang collaborates with scholars based in United States, Canada and Germany. Aixiang Jiang's co-authors include Yu Shyr, Duanqing Pei, David W. Scott, M. Kay Washington, Ryan D. Morin, Jeffrey Tang, Xing Wang, Jorma Keski‐Oja, Stephen J. Weiss and Kaisa Lehti and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Aixiang Jiang

40 papers receiving 2.7k citations

Hit Papers

A Probabilistic Classificatio... 2009 2026 2014 2020 2020 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aixiang Jiang United States 23 1.2k 1.1k 917 723 411 48 2.7k
Sidong Huang Canada 22 1.2k 0.9× 1.9k 1.6× 518 0.6× 621 0.9× 404 1.0× 44 2.9k
Zhan Yao United States 24 1.2k 1.0× 2.1k 1.8× 549 0.6× 501 0.7× 521 1.3× 39 2.9k
Outi Monni Finland 36 1.3k 1.0× 3.1k 2.7× 959 1.0× 1.2k 1.7× 637 1.5× 70 5.1k
Diana Mandelker United States 23 867 0.7× 1.3k 1.1× 388 0.4× 718 1.0× 482 1.2× 94 2.5k
Antonella Papa United States 18 855 0.7× 2.4k 2.1× 296 0.3× 560 0.8× 390 0.9× 29 3.1k
Ben Markman Australia 24 1.2k 1.0× 1.3k 1.2× 334 0.4× 329 0.5× 489 1.2× 75 2.5k
James M. Cleary United States 32 2.0k 1.6× 1.4k 1.2× 418 0.5× 524 0.7× 1.0k 2.5× 157 3.8k
Zijun Y. Xu‐Monette United States 27 1.5k 1.2× 857 0.7× 1.3k 1.4× 324 0.4× 202 0.5× 66 2.8k
Vanessa Rodrik-Outmezguine United States 16 943 0.8× 2.1k 1.9× 367 0.4× 458 0.6× 561 1.4× 32 2.8k
Natasha G. Deane United States 15 918 0.7× 1.3k 1.2× 528 0.6× 461 0.6× 273 0.7× 22 2.3k

Countries citing papers authored by Aixiang Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Aixiang Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aixiang Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Aixiang Jiang. A scholar is included among the top collaborators of Aixiang Jiang 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 Aixiang Jiang. Aixiang Jiang 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.
Rai, Shinya, Aixiang Jiang, Alexander M. Xu, et al.. (2025). Tumor microenvironment differences between diagnostic and relapsed classic Hodgkin lymphoma revealed by scRNA-seq. Blood Advances. 10(1). 29–38.
2.
Alduaij, Waleed, Laurie H. Sehn, Brett Collinge, et al.. (2025). Population-wide introduction of dose-adjusted EPOCH-R in high-grade B-cell lymphoma with MYC / BCL2 rearrangements, DLBCL morphology. Blood Advances. 10(2). 320–333.
3.
Li, Michael Y., Lauren C. Chong, Gerben Duns, et al.. (2024). TRAF3 loss-of-function reveals the noncanonical NF-κB pathway as a therapeutic target in diffuse large B cell lymphoma. Proceedings of the National Academy of Sciences. 121(18). e2320421121–e2320421121. 7 indexed citations
6.
Villa, Diego, Aixiang Jiang, Carlo Visco, et al.. (2023). Time to progression of disease and outcomes with second-line BTK inhibitors in relapsed/refractory mantle cell lymphoma. Blood Advances. 7(16). 4576–4585. 11 indexed citations
7.
Freeman, Ciara L., Ling Jin, Sriram Balasubramanian, et al.. (2022). Molecular determinants of outcomes in relapsed or refractory mantle cell lymphoma treated with ibrutinib or temsirolimus in the MCL3001 (RAY) trial. Leukemia. 36(10). 2479–2487. 3 indexed citations
8.
Nissen, Michael, Xuehai Wang, Clémentine Sarkozy, et al.. (2021). Immune Profiling of Diagnostic DLBCL Biopsies Dramatically Improves upon Cell-of-Origin Risk Stratification. Blood. 138(Supplement 1). 719–719.
9.
Jiang, Aixiang, Laura K. Hilton, Jeffrey Tang, et al.. (2020). PRPS-ST: A Protocol-Agnostic Self-training Method for Gene Expression–Based Classification of Blood Cancers. Blood Cancer Discovery. 1(3). 244–257. 6 indexed citations
10.
Hilton, Laura K., Jeffrey Tang, Susana Ben‐Neriah, et al.. (2019). The double-hit signature identifies double-hit diffuse large B-cell lymphoma with genetic events cryptic to FISH. Blood. 134(18). 1528–1532. 76 indexed citations
11.
Scott, David W., Rebecca L. King, Annette M. Staiger, et al.. (2018). High-grade B-cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements with diffuse large B-cell lymphoma morphology. Blood. 131(18). 2060–2064. 145 indexed citations
12.
Su, Yingjun, Anna E. Vilgelm, Mark C. Kelley, et al.. (2012). RAF265 Inhibits the Growth of Advanced Human Melanoma Tumors. Clinical Cancer Research. 18(8). 2184–2198. 47 indexed citations
13.
Miller, Todd W., Justin M. Balko, Emily M. Fox, et al.. (2011). ERα-Dependent E2F Transcription Can Mediate Resistance to Estrogen Deprivation in Human Breast Cancer. Cancer Discovery. 1(4). 338–351. 241 indexed citations
14.
Brantley‐Sieders, Dana M., Aixiang Jiang, Krishna Sarma, et al.. (2011). Eph/Ephrin Profiling in Human Breast Cancer Reveals Significant Associations between Expression Level and Clinical Outcome. PLoS ONE. 6(9). e24426–e24426. 112 indexed citations
15.
Brantley‐Sieders, Dana M., Meghana Rao, Sarah P. Short, et al.. (2010). Angiocrine Factors Modulate Tumor Proliferation and Motility through EphA2 Repression of Slit2 Tumor Suppressor Function in Endothelium. Cancer Research. 71(3). 976–987. 51 indexed citations
16.
Boone, Braden, et al.. (2010). Genomic profiling of C/EBPβ2 transformed mammary epithelial cells: A role for nuclear interleukin-1β. Cancer Biology & Therapy. 10(5). 509–519. 7 indexed citations
17.
Smith, J. Joshua, Natasha G. Deane, Fei Wu, et al.. (2009). Experimentally Derived Metastasis Gene Expression Profile Predicts Recurrence and Death in Patients With Colon Cancer. Gastroenterology. 138(3). 958–968. 562 indexed citations breakdown →
18.
Massion, Pierre P., Yong Zou, Heidi Chen, et al.. (2008). Smoking-related Genomic Signatures in Non–Small Cell Lung Cancer. American Journal of Respiratory and Critical Care Medicine. 178(11). 1164–1172. 35 indexed citations
20.
Lei, Jianxun, Aixiang Jiang, & Duanqing Pei. (1998). Identification and characterization of a new splicing variant of vascular endothelial growth factor: VEGF183. Biochimica et Biophysica Acta (BBA) - Gene Structure and Expression. 1443(3). 400–406. 70 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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