Jiang Yang

3.3k total citations · 1 hit paper
45 papers, 2.7k citations indexed

About

Jiang Yang is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Jiang Yang has authored 45 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 12 papers in Cancer Research and 9 papers in Oncology. Recurrent topics in Jiang Yang's work include Nanoparticle-Based Drug Delivery (6 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and RNA Interference and Gene Delivery (5 papers). Jiang Yang is often cited by papers focused on Nanoparticle-Based Drug Delivery (6 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and RNA Interference and Gene Delivery (5 papers). Jiang Yang collaborates with scholars based in United States, China and Austria. Jiang Yang's co-authors include Marsha A. Moses, Roopali Roy, Peng Guo, Debra T. Auguste, Jing Huang, David Zurakowski, Daxing Liu, Di Jia, Cecilia A. Fernández and Biran Wang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Jiang Yang

43 papers receiving 2.7k citations

Hit Papers

Matrix Metalloproteinases As Novel Biomarker s and Potent... 2009 2026 2014 2020 2009 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiang Yang United States 19 1.3k 708 678 433 392 45 2.7k
Troy A. Baudino United States 26 2.6k 1.9× 869 1.2× 607 0.9× 318 0.7× 302 0.8× 43 4.5k
Andrea Petretto Italy 34 1.5k 1.1× 675 1.0× 351 0.5× 196 0.5× 359 0.9× 136 3.6k
Chryso Kanthou United Kingdom 29 1.7k 1.3× 614 0.9× 698 1.0× 175 0.4× 441 1.1× 61 3.4k
Danilo Marimpietri Italy 30 1.5k 1.1× 578 0.8× 459 0.7× 396 0.9× 293 0.7× 67 2.6k
Diane R. Bielenberg United States 40 3.1k 2.3× 1.9k 2.7× 1.1k 1.6× 303 0.7× 396 1.0× 95 5.5k
Zehong Cao United States 20 1.2k 0.9× 342 0.5× 325 0.5× 501 1.2× 572 1.5× 28 2.7k
Nicole Anderson United States 15 1.1k 0.8× 734 1.0× 708 1.0× 125 0.3× 378 1.0× 34 2.7k
Kevin G. Chen United States 34 1.9k 1.4× 977 1.4× 316 0.5× 129 0.3× 450 1.1× 67 3.2k
Fabio Pastorino Italy 36 2.1k 1.5× 803 1.1× 652 1.0× 614 1.4× 462 1.2× 90 3.5k
David A. Hess Canada 34 1.8k 1.4× 1.1k 1.6× 659 1.0× 179 0.4× 254 0.6× 125 4.2k

Countries citing papers authored by Jiang Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jiang Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiang Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Jiang Yang. A scholar is included among the top collaborators of Jiang Yang 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 Jiang Yang. Jiang Yang 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
3.
Liu, Junying, et al.. (2020). Efficacy and safety of nebivolol in hypertensive patients: a meta-analysis of randomized controlled trials. Journal of International Medical Research. 48(10). 1220731177–1220731177. 8 indexed citations
4.
Roy, Roopali, Alisa Stephens, Cassandra Daisy, et al.. (2020). Association of Longitudinal Changes in Symptoms and Urinary Biomarkers in Patients with Urological Chronic Pelvic Pain Syndrome: A MAPP Research Network Study. The Journal of Urology. 205(2). 514–523. 5 indexed citations
5.
Peng, Cong, Hua Yang, Qian Ran, et al.. (2020). Immediate Abnormal Intrinsic Brain Activity Patterns in Patients with End-stage Renal Disease During a Single Dialysis Session. Clinical Neuroradiology. 31(2). 373–381. 10 indexed citations
6.
Vickman, Renee E., Jiang Yang, Nadia A. Lanman, et al.. (2019). Cholesterol Sulfotransferase SULT2B1b Modulates Sensitivity to Death Receptor Ligand TNFα in Castration-Resistant Prostate Cancer. Molecular Cancer Research. 17(6). 1253–1263. 8 indexed citations
7.
Yang, Jiang, et al.. (2019). Distinct expression patterns of SULT2B1b in human prostate epithelium. The Prostate. 79(11). 1256–1266. 4 indexed citations
8.
Yang, Jiang, Xiaowei Ma, Yanlin Tan, Qingqing Lu, & Yunhua Wang. (2019). Hamartoma of Mature Cardiac Myocytes Mimicking Malignancy on 18F-FDG PET/CT Images. Clinical Nuclear Medicine. 44(11). 892–894. 5 indexed citations
9.
Yang, Jiang, Munir M. Zaman, Iliyan Vlasakov, et al.. (2019). Adipocytes promote ovarian cancer chemoresistance. Scientific Reports. 9(1). 13316–13316. 78 indexed citations
10.
Yang, Jiang, et al.. (2018). A Young Man with a Mass: Non-Early Precursor T-Cell Lymphoblastic Lymphoma. The American Journal of Medicine. 132(1). 58–60.
11.
Guo, Peng, Biran Wang, Daxing Liu, et al.. (2018). Using Atomic Force Microscopy to Predict Tumor Specificity of ICAM1 Antibody-Directed Nanomedicines. Nano Letters. 18(4). 2254–2262. 13 indexed citations
12.
Guo, Peng, Jiang Yang, Diane R. Bielenberg, et al.. (2017). A quantitative method for screening and identifying molecular targets for nanomedicine. Journal of Controlled Release. 263. 57–67. 12 indexed citations
13.
Curatolo, Adam S., Monisha Sachdev, Alisa Stephens, et al.. (2017). Identification of novel non‐invasive biomarkers of urinary chronic pelvic pain syndrome: findings from the Multidisciplinary Approach to the Study of Chronic Pelvic Pain ( MAPP ) Research Network. British Journal of Urology. 120(1). 130–142. 29 indexed citations
14.
Yang, Jiang, Roopali Roy, Andrej Jedinak, & Marsha A. Moses. (2015). Mining the Human Proteome. The Cancer Journal. 21(4). 327–336. 12 indexed citations
15.
Li, Hui, et al.. (2015). Aldehyde Dehydragenase 1 and Nodal as Significant Prognostic Markers in Colorectal Cancer. Pathology & Oncology Research. 22(1). 121–127. 4 indexed citations
16.
Guo, Peng, Jing Huang, Liya Wang, et al.. (2014). ICAM-1 as a molecular target for triple negative breast cancer. Proceedings of the National Academy of Sciences. 111(41). 14710–14715. 154 indexed citations
17.
Guo, Peng, Jin‐Oh You, Jiang Yang, et al.. (2014). Inhibiting Metastatic Breast Cancer Cell Migration via the Synergy of Targeted, pH-triggered siRNA Delivery and Chemokine Axis Blockade. Molecular Pharmaceutics. 11(3). 755–765. 64 indexed citations
18.
Guo, Peng, Jin‐Oh You, Jiang Yang, Marsha A. Moses, & Debra T. Auguste. (2012). Using breast cancer cell CXCR4 surface expression to predict liposome binding and cytotoxicity. Biomaterials. 33(32). 8104–8110. 38 indexed citations
19.
Coticchia, Christine M., Adam S. Curatolo, David Zurakowski, et al.. (2011). Urinary MMP-2 and MMP-9 predict the presence of ovarian cancer in women with normal CA125 levels. Gynecologic Oncology. 123(2). 295–300. 46 indexed citations
20.
Yang, Jiang, Kaori Sato, Tamar Aprahamian, et al.. (2004). Endothelial Overexpression of Fas Ligand Decreases Atherosclerosis in Apolipoprotein E–Deficient Mice. Arteriosclerosis Thrombosis and Vascular Biology. 24(8). 1466–1473. 19 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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