Dan Hua

702 total citations
21 papers, 450 citations indexed

About

Dan Hua is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Dan Hua has authored 21 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 14 papers in Cancer Research and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Dan Hua's work include MicroRNA in disease regulation (7 papers), Circular RNAs in diseases (7 papers) and RNA modifications and cancer (6 papers). Dan Hua is often cited by papers focused on MicroRNA in disease regulation (7 papers), Circular RNAs in diseases (7 papers) and RNA modifications and cancer (6 papers). Dan Hua collaborates with scholars based in China and Montenegro. Dan Hua's co-authors include Cuiyun Sun, Shizhu Yu, Xuexia Zhou, Cuijuan Shi, Wenjun Luo, Lin Yu, Chun Rao, Zhendong Jiang, Xuebing Li and Qian Wang and has published in prestigious journals such as Journal of Clinical Investigation, American Journal Of Pathology and British Journal of Cancer.

In The Last Decade

Dan Hua

19 papers receiving 447 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dan Hua China 12 384 266 38 34 28 21 450
Benshuai You China 10 257 0.7× 177 0.7× 32 0.8× 32 0.9× 12 0.4× 16 353
Xiaozhu Tang China 8 439 1.1× 298 1.1× 47 1.2× 30 0.9× 15 0.5× 18 490
Youzhi Wu China 8 269 0.7× 212 0.8× 26 0.7× 22 0.6× 9 0.3× 17 352
Wenzheng Luo China 10 264 0.7× 243 0.9× 27 0.7× 20 0.6× 9 0.3× 12 352
Maode Wang China 8 230 0.6× 198 0.7× 53 1.4× 32 0.9× 10 0.4× 18 322
Zhijian Yue China 12 263 0.7× 200 0.8× 70 1.8× 18 0.5× 13 0.5× 20 383
Cinzia Caggiano Italy 11 259 0.7× 154 0.6× 41 1.1× 15 0.4× 9 0.3× 17 348

Countries citing papers authored by Dan Hua

Since Specialization
Citations

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

Fields of papers citing papers by Dan Hua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Hua

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Hua. A scholar is included among the top collaborators of Dan Hua 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 Dan Hua. Dan Hua 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.
Sun, Cuiyun, Qian Wang, Dan Hua, et al.. (2025). Hypoxia-induced S100A10 promotes glioblastoma malignancy and chemoresistance by activating PI3K-AKT signaling pathway. Functional & Integrative Genomics. 25(1). 202–202.
2.
Wang, Yixuan, Cuiyun Sun, Qian Wang, et al.. (2025). ZNRF2 is essential for gliomagenesis through orchestrating glycolysis and acts as a promising therapeutic target in glioma. Journal of Translational Medicine. 23(1). 185–185. 1 indexed citations
3.
4.
He, Yifan, Hailong Shi, Xingmei Zhu, et al.. (2024). Investigating the molecular mechanism of vitexin targeting CDK1 to inhibit colon cancer cell proliferation via GEO chip data mining, computer simulation, and biological activity verification. Naunyn-Schmiedeberg s Archives of Pharmacology. 398(2). 1637–1652. 2 indexed citations
5.
Pan, Hongli, Hua Huang, Qiang Chen, et al.. (2023). Identification of SRSF10 as a promising prognostic biomarker with functional significance among SRSFs for glioma. Life Sciences. 338. 122392–122392. 8 indexed citations
6.
Shi, Cuijuan, Wenjun Luo, Cuiyun Sun, et al.. (2023). The miR‐29 family members induce glioblastoma cell apoptosis by targeting cell division cycle 42 in a p53‐dependent manner. European Journal of Clinical Investigation. 53(6). e13964–e13964. 2 indexed citations
7.
Zhou, Xuexia, Xuebing Li, Run Wang, et al.. (2022). Recruitment of LEF1 by Pontin chromatin modifier amplifies TGFBR2 transcription and activates TGFβ/SMAD signalling during gliomagenesis. Cell Death and Disease. 13(9). 818–818. 3 indexed citations
8.
Wang, Run, Xuebing Li, Cuiyun Sun, et al.. (2021). The ATPase Pontin is a key cell cycle regulator by amplifying E2F1 transcription response in glioma. Cell Death and Disease. 12(2). 141–141. 11 indexed citations
9.
Hua, Dan, Tang Li-da, Wei‐Ting Wang, et al.. (2020). Improved Antiglioblastoma Activity and BBB Permeability by Conjugation of Paclitaxel to a Cell‐Penetrative MMP‐2‐Cleavable Peptide. Advanced Science. 8(3). 2001960–2001960. 41 indexed citations
10.
Hua, Dan, Qian Zhao, Yang Yu, et al.. (2020). Eucalyptal A inhibits glioma by rectifying oncogenic splicing of MYO1B mRNA via suppressing SRSF1 expression. European Journal of Pharmacology. 890. 173669–173669. 10 indexed citations
11.
Zhou, Xuexia, Xuebing Li, Lin Yu, et al.. (2019). The RNA-binding protein SRSF1 is a key cell cycle regulator via stabilizing NEAT1 in glioma. The International Journal of Biochemistry & Cell Biology. 113. 75–86. 41 indexed citations
12.
Shi, Cuijuan, Chun Rao, Cuiyun Sun, et al.. (2018). miR-29s function as tumor suppressors in gliomas by targeting TRAF4 and predict patient prognosis. Cell Death and Disease. 9(11). 1078–1078. 17 indexed citations
13.
Liu, Jing, Jie Yang, Lin Yu, et al.. (2018). miR-361-5p inhibits glioma migration and invasion by targeting SND1. OncoTargets and Therapy. Volume 11. 5239–5252. 22 indexed citations
14.
Zhou, Xuexia, Run Wang, Xuebing Li, et al.. (2018). Splicing factor SRSF1 promotes gliomagenesis via oncogenic splice-switching of MYO1B. Journal of Clinical Investigation. 129(2). 676–693. 109 indexed citations
15.
Luo, Wenjun, Cuiyun Sun, Junhu Zhou, et al.. (2018). miR-135a-5p Functions as a Glioma Proliferation Suppressor by Targeting Tumor Necrosis Factor Receptor–Associated Factor 5 and Predicts Patients' Prognosis. American Journal Of Pathology. 189(1). 162–176. 19 indexed citations
16.
Hua, Dan, Wen Luo, James J.‐W. Duan, et al.. (2018). Screening and identification of potent α-glycosidase inhibitors from Gardenia jasminoides Ellis. South African Journal of Botany. 119. 377–382. 8 indexed citations
17.
Li, Huining, Lin Yu, Jing Liu, et al.. (2017). miR-320a functions as a suppressor for gliomas by targeting SND1 and β-catenin, and predicts the prognosis of patients. Oncotarget. 8(12). 19723–19737. 44 indexed citations
18.
Shi, Cuijuan, Linlin Ren, Cuiyun Sun, et al.. (2017). miR-29a/b/c function as invasion suppressors for gliomas by targeting CDC42 and predict the prognosis of patients. British Journal of Cancer. 117(7). 1036–1047. 50 indexed citations
19.
Zhou, Xuexia, Xuebing Li, Cuiyun Sun, et al.. (2017). Quaking-5 suppresses aggressiveness of lung cancer cells through inhibiting β-catenin signaling pathway. Oncotarget. 8(47). 82174–82184. 28 indexed citations
20.
Gong, Min, Dan Hua, Weiling Kong, et al.. (2014). Potent tumor targeting drug release system comprising MMP-2 specific peptide fragment with self-assembling characteristics. Drug Design Development and Therapy. 8. 1839–1839. 11 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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