Jin Yang

1.9k total citations · 1 hit paper
68 papers, 1.3k citations indexed

About

Jin Yang is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Jin Yang has authored 68 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Oncology, 25 papers in Pulmonary and Respiratory Medicine and 16 papers in Molecular Biology. Recurrent topics in Jin Yang's work include Lung Cancer Treatments and Mutations (12 papers), HER2/EGFR in Cancer Research (9 papers) and Cancer-related molecular mechanisms research (6 papers). Jin Yang is often cited by papers focused on Lung Cancer Treatments and Mutations (12 papers), HER2/EGFR in Cancer Research (9 papers) and Cancer-related molecular mechanisms research (6 papers). Jin Yang collaborates with scholars based in China, United States and Netherlands. Jin Yang's co-authors include Jun Lyu, Qingqing Liu, Yuanjie Li, Shuai Zheng, Tianyi Wang, Li Li, Aozi Feng, Juan Li, Peijun Liu and Xiaona Mao and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Scientific Reports.

In The Last Decade

Jin Yang

64 papers receiving 1.3k citations

Hit Papers

Brief introduction of medical database and data mining te... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jin Yang China 20 411 406 334 255 184 68 1.3k
Yoon Ho Ko South Korea 23 591 1.4× 514 1.3× 375 1.1× 401 1.6× 173 0.9× 103 1.5k
Andrew Borkowski United States 20 597 1.5× 382 0.9× 439 1.3× 244 1.0× 177 1.0× 39 1.5k
Ming Jin China 20 643 1.6× 452 1.1× 225 0.7× 351 1.4× 234 1.3× 79 1.5k
Maria Rosaria Giovagnoli Italy 22 415 1.0× 314 0.8× 353 1.1× 475 1.9× 329 1.8× 92 1.4k
Zhongfa Zhang China 24 951 2.3× 342 0.8× 426 1.3× 427 1.7× 218 1.2× 57 2.0k
Supriya Gupta United States 12 573 1.4× 822 2.0× 268 0.8× 412 1.6× 83 0.5× 48 1.6k
William K. Murray Australia 19 415 1.0× 767 1.9× 292 0.9× 118 0.5× 293 1.6× 39 1.5k
Naruto Taira Japan 23 400 1.0× 796 2.0× 338 1.0× 436 1.7× 194 1.1× 144 1.5k
Chenjing Zhu China 19 313 0.8× 476 1.2× 226 0.7× 197 0.8× 149 0.8× 46 1.3k
Choong‐kun Lee South Korea 21 535 1.3× 688 1.7× 490 1.5× 312 1.2× 351 1.9× 100 1.6k

Countries citing papers authored by Jin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Yang. A scholar is included among the top collaborators of Jin 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 Jin Yang. Jin 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
1.
Li, Jianbin, Shu Wang, Shaohua Zhang, et al.. (2025). Chinese expert consensus on clinical diagnosis and treatment of breast cancer targeting HER2. PubMed. 6. 21–21. 1 indexed citations
3.
Li, Yiqun, Zhongsheng Tong, Quchang Ouyang, et al.. (2023). Real‐world treatment patterns and outcomes of pyrotinib‐based therapy in patients with HER2‐positive advanced breast cancer (PRETTY): A nationwide, prospective, observational study. International Journal of Cancer. 153(10). 1809–1818. 5 indexed citations
5.
Dû, Lê Thi Huong, Ning Liu, Jianfeng Jin, et al.. (2022). ZNF3 regulates proliferation, migration and invasion through MMP1 and TWIST in colorectal cancer. Acta Biochimica et Biophysica Sinica. 54(12). 1889–1896. 7 indexed citations
6.
Bao, Zhiyao, Lifeng Luo, Tian Xu, et al.. (2022). Risk factors and prognostic role of renal adverse event in patients receiving immune checkpoint inhibitor therapy: analysis of data from a retrospective cohort study. Annals of Translational Medicine. 10(18). 967–967. 5 indexed citations
7.
Shen, Yanwei, et al.. (2021). Angiomotin-p130 inhibits vasculogenic mimicry formation of small cell lung cancer independently of Smad2/3 signal pathway. Journal of Bioenergetics and Biomembranes. 53(3). 295–305. 6 indexed citations
8.
Liu, Qingqing, Jin Yang, Jun Zhang, et al.. (2019). Description of Clinical Characteristics of VAP Patients in MIMIC Database. Frontiers in Pharmacology. 10. 62–62. 7 indexed citations
9.
Wang, Na, Jin Yang, Qingqing Liu, et al.. (2019). Insurance status is related to overall survival in patients with small intestine adenocarcinoma: A population-based study. Current Problems in Cancer. 44(1). 100505–100505. 6 indexed citations
10.
Chen, Siying, Yang Liu, Jin Yang, et al.. (2019). Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer. Frontiers in Oncology. 9. 361–361. 47 indexed citations
11.
Yang, Jin, et al.. (2018). Predictors of breast cancer cell types and their prognostic power in breast cancer patients. BMC Genomics. 19(1). 137–137. 12 indexed citations
12.
Liu, Qingqing, et al.. (2018). Associations between interleukin-10 polymorphisms and susceptibility to rheumatoid arthritis: a meta-analysis and meta-regression. Clinical Rheumatology. 37(12). 3229–3237. 12 indexed citations
13.
Mao, Xiaona, Pingping Li, Yaochun Wang, et al.. (2017). CRB3 regulates contact inhibition by activating the Hippo pathway in mammary epithelial cells. Cell Death and Disease. 8(1). e2546–e2546. 36 indexed citations
14.
Zhang, Yichen, E‐E Ke, Zhihong Chen, et al.. (2017). P3.02b-095 Tracing Spatiotemporal T790M Heterogeneity in Patients with EGFR-Mutant Advanced NSCLC after Acquired Resistance to EGFR TKIs. Journal of Thoracic Oncology. 12(1). S1249–S1249.
15.
Liu, Jie, Juan Li, Pingping Li, et al.. (2017). Loss of DLG5 promotes breast cancer malignancy by inhibiting the Hippo signaling pathway. Scientific Reports. 7(1). 42125–42125. 51 indexed citations
16.
Wu, Yi‐Long, Jin Yang, Caicun Zhou, et al.. (2017). PL03.05: BRAIN: A Phase III Trial Comparing WBI and Chemotherapy with Icotinib in NSCLC with Brain Metastases Harboring EGFR Mutations (CTONG 1201). Journal of Thoracic Oncology. 12(1). S6–S6. 17 indexed citations
17.
Yang, Jiao, Shuting Li, Biyuan Wang, et al.. (2016). Potential biomarkers for anti-EGFR therapy in metastatic colorectal cancer. Tumor Biology. 37(9). 11645–11655. 21 indexed citations
18.
Wang, Xin, Yanwei Shen, Shuting Li, et al.. (2016). Importance of the interaction between immune cells and tumor vasculature mediated by thalidomide in cancer treatment (Review). International Journal of Molecular Medicine. 38(4). 1021–1029. 19 indexed citations
19.
Lv, Meng, Ling Chen, Tianjie Qin, et al.. (2015). Angiomotin promotes breast cancer cell proliferation and invasion. Oncology Reports. 33(4). 1938–1946. 25 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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