Zhengyan Chang

551 total citations
24 papers, 409 citations indexed

About

Zhengyan Chang is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Zhengyan Chang has authored 24 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 12 papers in Cancer Research and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Zhengyan Chang's work include MicroRNA in disease regulation (8 papers), Cancer-related molecular mechanisms research (8 papers) and RNA modifications and cancer (7 papers). Zhengyan Chang is often cited by papers focused on MicroRNA in disease regulation (8 papers), Cancer-related molecular mechanisms research (8 papers) and RNA modifications and cancer (7 papers). Zhengyan Chang collaborates with scholars based in China. Zhengyan Chang's co-authors include Yu‐Shui Ma, Da Fu, Gai‐Xia Lu, Zhongwei Lv, Fei Yu, Xianling Cong, Ruting Xie, Huiqiong Yang, Jian Zhu and Qing Wei and has published in prestigious journals such as PLoS ONE, Oncotarget and Neuro-Oncology.

In The Last Decade

Zhengyan Chang

22 papers receiving 409 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhengyan Chang China 13 312 235 64 47 31 24 409
Yun Gu China 11 284 0.9× 227 1.0× 42 0.7× 36 0.8× 45 1.5× 22 384
Jing Lan China 10 315 1.0× 187 0.8× 71 1.1× 38 0.8× 20 0.6× 24 418
Yvan de Féraudy France 3 326 1.0× 277 1.2× 44 0.7× 23 0.5× 29 0.9× 6 434
Xiangqian Zheng China 11 389 1.2× 299 1.3× 90 1.4× 55 1.2× 44 1.4× 25 510
Runyi Ye China 12 192 0.6× 142 0.6× 66 1.0× 45 1.0× 29 0.9× 15 306
Feiye Liu China 9 213 0.7× 148 0.6× 44 0.7× 23 0.5× 19 0.6× 13 294
Dongli Zhao China 10 241 0.8× 154 0.7× 59 0.9× 38 0.8× 33 1.1× 21 350
Haitao Zhang China 11 221 0.7× 172 0.7× 53 0.8× 30 0.6× 25 0.8× 25 340

Countries citing papers authored by Zhengyan Chang

Since Specialization
Citations

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

Fields of papers citing papers by Zhengyan Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhengyan Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhengyan Chang. A scholar is included among the top collaborators of Zhengyan Chang 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 Zhengyan Chang. Zhengyan Chang 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.
Chang, Le, et al.. (2025). Single-cell RNA sequencing and multi-omics analysis of prognosis-related staging in papillary thyroid cancer. Cancer Immunology Immunotherapy. 74(8). 267–267.
2.
Chang, Zhengyan, Yefei Zhu, Ping Wang, et al.. (2025). Multi-omic analyses of the development of obesity-related depression linked to the gut microbe Anaerotruncus colihominis and its metabolite glutamate. Science Bulletin. 70(11). 1822–1833. 3 indexed citations
3.
Yin, Huabin, Tong Su, Jiali Jin, et al.. (2024). Clinical-proteomic classification and precision treatment strategy of chordoma. Cell Reports Medicine. 5(10). 101757–101757. 2 indexed citations
4.
Chang, Zhengyan, Runzhi Huang, Zhenyu Li, et al.. (2024). Modulation of SRC by SNTB1 activates the Hippo-YAP pathway during colon adenocarcinoma metastasis. Journal of Translational Medicine. 22(1). 1029–1029.
5.
Chang, Zhengyan, et al.. (2024). Multi-omics analysis-based macrophage differentiation-associated papillary thyroid cancer patient classifier. Translational Oncology. 43. 101889–101889. 9 indexed citations
6.
Zhang, Jingcheng, Wentao Zhang, Yufeng Jiang, et al.. (2023). Emerging roles and potential application of PIWI-interacting RNA in urological tumors. Frontiers in Endocrinology. 13. 6 indexed citations
7.
Huang, Runzhi, Zhiwei Zeng, Jie Zhang, et al.. (2022). The Identification of Prognostic and Metastatic Alternative Splicing in Skin Cutaneous Melanoma. Cancer Control. 29. 2895469602–2895469602. 3 indexed citations
8.
Huang, Runzhi, Shuyuan Xian, Dianwen Song, et al.. (2022). The role of toll-like receptors (TLRs) in pan-cancer. Annals of Medicine. 54(1). 1918–1937. 13 indexed citations
9.
Meng, Tong, Runzhi Huang, Jiali Jin, et al.. (2021). A comparative integrated multi-omics analysis identifies CA2 as a novel target for chordoma. Neuro-Oncology. 23(10). 1709–1722. 20 indexed citations
10.
Zheng, Zixuan, Penghui Yan, Dianwen Song, et al.. (2021). Identification of prognostic and bone metastasis‐related alternative splicing signatures in mesothelioma. Cancer Medicine. 10(13). 4478–4492. 3 indexed citations
11.
Ma, Yu‐Shui, Xiaofeng Wang, Yunjie Zhang, et al.. (2020). Inhibition of USP14 Deubiquitinating Activity as a Potential Therapy for Tumors with p53 Deficiency. Molecular Therapy — Oncolytics. 16. 147–157. 26 indexed citations
12.
Chang, Zhengyan, Runzhi Huang, Jiehan Li, et al.. (2020). The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Colon Adenocarcinoma Metastasis. Frontiers in Cell and Developmental Biology. 8. 688–688. 36 indexed citations
13.
14.
Chang, Zhengyan, Runzhi Huang, Hong Chen, et al.. (2020). PIWI-interacting RNAs piR-13643 and piR-21238 are promising diagnostic biomarkers of papillary thyroid carcinoma. Aging. 12(10). 9292–9310. 17 indexed citations
15.
Xie, Ruting, Xianling Cong, Xiaoming Zhong, et al.. (2018). MicroRNA-33a downregulation is associated with tumorigenesis and poor prognosis in patients with hepatocellular carcinoma. Oncology Letters. 15(4). 4571–4577. 18 indexed citations
16.
Ma, Yu‐Shui, Huiqiong Yang, Shaobo Xue, et al.. (2018). Reduced hsa-miR-124-3p levels are associated with the poor survival of patients with hepatocellular carcinoma. Molecular Biology Reports. 45(6). 2615–2623. 40 indexed citations
17.
Ma, Yu‐Shui, Zhongwei Lv, Fei Yu, et al.. (2018). MicroRNA-302a/d inhibits the self-renewal capability and cell cycle entry of liver cancer stem cells by targeting the E2F7/AKT axis. Journal of Experimental & Clinical Cancer Research. 37(1). 252–252. 64 indexed citations
18.
Chang, Zhengyan, Yaohui Gao, Qianyu Li, et al.. (2017). Anoctamin5 regulates cell migration and invasion in thyroid cancer. International Journal of Oncology. 51(4). 1311–1319. 29 indexed citations
19.
Hou, Likun, Yu‐Shui Ma, Yang Han, et al.. (2017). Association of microRNA-33a Molecular Signature with Non-Small Cell Lung Cancer Diagnosis and Prognosis after Chemotherapy. PLoS ONE. 12(1). e0170431–e0170431. 28 indexed citations
20.
Sun, Ran, Yu‐Shui Ma, Shengyu Feng, et al.. (2014). Differential expression profiling of microRNAs in para-carcinoma, carcinoma and relapse human pancreatic cancer. Clinical & Translational Oncology. 17(5). 398–408. 8 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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