Yuming Liu

2.4k total citations
68 papers, 1.7k citations indexed

About

Yuming Liu is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Yuming Liu has authored 68 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 11 papers in Pulmonary and Respiratory Medicine and 11 papers in Oncology. Recurrent topics in Yuming Liu's work include Cellular Mechanics and Interactions (8 papers), Cancer Cells and Metastasis (8 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (5 papers). Yuming Liu is often cited by papers focused on Cellular Mechanics and Interactions (8 papers), Cancer Cells and Metastasis (8 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (5 papers). Yuming Liu collaborates with scholars based in United States, China and Taiwan. Yuming Liu's co-authors include Kevin W. Eliceiri, Cole R. Drifka, Adib Keikhosravi, Guneet S. Mehta, Weiyuan John Kao, Agnes G. Loeffler, Jun‐Shan Yang, Qinghua Liu, Patricia J. Keely and Gareth J. Thomas and has published in prestigious journals such as Nature Communications, PLoS ONE and Scientific Reports.

In The Last Decade

Yuming Liu

64 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuming Liu United States 20 469 410 357 269 177 68 1.7k
Chiara Arienti Italy 20 788 1.7× 717 1.7× 742 2.1× 186 0.7× 152 0.9× 42 2.0k
Michele Zanoni Italy 21 758 1.6× 708 1.7× 693 1.9× 170 0.6× 124 0.7× 43 2.0k
Violetta Filas Poland 15 530 1.1× 511 1.2× 593 1.7× 147 0.5× 118 0.7× 43 1.7k
Amirali B. Bukhari India 12 347 0.7× 730 1.8× 329 0.9× 102 0.4× 189 1.1× 15 1.7k
Kandice Tanner United States 24 390 0.8× 443 1.1× 696 1.9× 721 2.7× 179 1.0× 46 1.7k
Nina Kramer Austria 16 855 1.8× 874 2.1× 643 1.8× 302 1.1× 134 0.8× 24 2.2k
Jonathan B. Fitzgerald United States 22 643 1.4× 1.0k 2.5× 409 1.1× 157 0.6× 419 2.4× 50 2.4k
Nikolay Nikolsky Russia 25 256 0.5× 1.1k 2.6× 133 0.4× 263 1.0× 84 0.5× 87 2.2k
Shoutian Zhu United States 21 398 0.8× 1.4k 3.5× 266 0.7× 325 1.2× 153 0.9× 33 2.7k
Valérie Lobjois France 22 471 1.0× 987 2.4× 406 1.1× 461 1.7× 36 0.2× 58 1.9k

Countries citing papers authored by Yuming Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yuming Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuming Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Yuming Liu. A scholar is included among the top collaborators of Yuming Liu 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 Yuming Liu. Yuming Liu 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.
Liu, Jingyu, Yongyou Hu, Xian Li, et al.. (2025). Unlocking the power of manganese-doped MoS2 hollow nanotubes: A game-changing Fenton co-catalyst for ciprofloxacin degradation. Chemical Engineering Journal. 511. 162009–162009. 2 indexed citations
2.
Boucau, Julie, Threnesan Naidoo, Yuming Liu, et al.. (2025). Inflammatory Macrophages Associate With Tissue Injury and Fibrosis in a Mouse Model of Tuberculosis. The Journal of Infectious Diseases. 232(6). 1375–1388.
3.
4.
Li, Shimeng, Zhichao Liu, Xiaodan Jiao, et al.. (2024). Selpercatinib attenuates bleomycin-induced pulmonary fibrosis by inhibiting the TGF-β1 signaling pathway. Biochemical Pharmacology. 225. 116282–116282. 2 indexed citations
5.
Guo, Xiaowei, Wenqi Li, Tiantian Zhang, et al.. (2024). Remdesivir alleviates skin fibrosis by suppressing TGF-β1 signaling pathway. PLoS ONE. 19(7). e0305927–e0305927. 3 indexed citations
6.
Xue, Tongtong, Qianyi Zhang, Tiantian Zhang, et al.. (2024). Zafirlukast ameliorates lipopolysaccharide and bleomycin-induced lung inflammation in mice. BMC Pulmonary Medicine. 24(1). 456–456. 4 indexed citations
7.
Liu, Yuming, et al.. (2023). SSH1 promotes progression of intrahepatic cholangiocarcinoma via p38 MAPK-CXCL8 axis. Carcinogenesis. 44(3). 232–241. 4 indexed citations
8.
Wu, Yue, Yanyi Li, Kaiming Li, et al.. (2023). Vitamin D receptor (VDR) mediates the quiescence of activated hepatic stellate cells (aHSCs) by regulating M2 macrophage exosomal smooth muscle cell-associated protein 5 (SMAP-5). Journal of Zhejiang University SCIENCE B. 24(3). 248–261. 13 indexed citations
9.
10.
Drifka, Cole R., Kelli B. Pointer, Yuming Liu, et al.. (2021). Navigating the Collagen Jungle: The Biomedical Potential of Fiber Organization in Cancer. Bioengineering. 8(2). 17–17. 62 indexed citations
11.
Schmuck, Eric G., Sushmita Roy, Tianhua Zhou, et al.. (2021). Cultured cardiac fibroblasts and myofibroblasts express Sushi Containing Domain 2 and assemble a unique fibronectin rich matrix. Experimental Cell Research. 399(2). 112489–112489. 4 indexed citations
12.
Zhang, Ming, Jian Wang, Kaixiang Zhang, et al.. (2021). Ten-eleven translocation 1 mediated-DNA hydroxymethylation is required for myelination and remyelination in the mouse brain. Nature Communications. 12(1). 5091–5091. 39 indexed citations
13.
Xu, Tao, Liang‐yun Li, Shuang Hu, et al.. (2020). MicroRNA‐708 modulates Hepatic Stellate Cells activation and enhances extracellular matrix accumulation via direct targeting TMEM88. Journal of Cellular and Molecular Medicine. 24(13). 7127–7140. 16 indexed citations
14.
Gu, Feng, Yuming Liu, Yuming Liu, et al.. (2020). Distinct functions and prognostic values of RORs in gastric cancer. Open Medicine. 15(1). 424–434. 1 indexed citations
15.
Keikhosravi, Adib, Bin Li, Yuming Liu, & Kevin W. Eliceiri. (2019). Intensity-based registration of bright-field and second-harmonic generation images of histopathology tissue sections. Biomedical Optics Express. 11(1). 160–160. 16 indexed citations
16.
Best, Sara L., Yuming Liu, Adib Keikhosravi, et al.. (2019). Collagen organization of renal cell carcinoma differs between low and high grade tumors. BMC Cancer. 19(1). 490–490. 39 indexed citations
17.
Keikhosravi, Adib, Yuming Liu, Cole R. Drifka, et al.. (2017). Quantification of collagen organization in histopathology samples using liquid crystal based polarization microscopy. Biomedical Optics Express. 8(9). 4243–4243. 40 indexed citations
18.
Squirrell, Jayne M., et al.. (2015). Endogenous Optical Signals Reveal Changes of Elastin and Collagen Organization During Differentiation of Mouse Embryonic Stem Cells. Tissue Engineering Part C Methods. 21(10). 995–1004. 7 indexed citations
19.
He, Ying, Shen Xianrong, Yuming Liu, et al.. (2014). Serum metabonomics of rats irradiated by low-dose γ-rays. Jiefangjun yixue zazhi. 39(7). 517–521. 1 indexed citations
20.
Yang, Kailin, Pin‐I Huang, Tai‐Tong Wong, et al.. (2010). Long-Term Outcomes of Radiotherapy for Primary Pediatric Brain Tumors: Statistics and Strategies of a Single Institute in Taiwan. 17(2). 85–99. 3 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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