Meiru Hu

1.8k total citations
56 papers, 1.4k citations indexed

About

Meiru Hu is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Meiru Hu has authored 56 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 21 papers in Oncology and 10 papers in Immunology. Recurrent topics in Meiru Hu's work include Glycosylation and Glycoproteins Research (7 papers), Cancer-related Molecular Pathways (7 papers) and Monoclonal and Polyclonal Antibodies Research (7 papers). Meiru Hu is often cited by papers focused on Glycosylation and Glycoproteins Research (7 papers), Cancer-related Molecular Pathways (7 papers) and Monoclonal and Polyclonal Antibodies Research (7 papers). Meiru Hu collaborates with scholars based in China, United States and Russia. Meiru Hu's co-authors include Lun Song, Bing Shen, Ning Guo, Ming Shi, Ming Yu, Yuanfang Ma, Qian Lu, Dan Liu, Changguo Chen and Shasha Liu and has published in prestigious journals such as Nucleic Acids Research, The Journal of Immunology and PLoS ONE.

In The Last Decade

Meiru Hu

56 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Meiru Hu China 22 694 438 247 205 178 56 1.4k
Takeo Sakurai Japan 25 641 0.9× 369 0.8× 328 1.3× 129 0.6× 70 0.4× 112 1.9k
Isabel Tritschler Switzerland 12 1.1k 1.6× 518 1.2× 445 1.8× 746 3.6× 211 1.2× 15 2.6k
Ryuichi Fukuyama Japan 26 833 1.2× 226 0.5× 109 0.4× 101 0.5× 85 0.5× 62 1.6k
Claudia Lanari Argentina 29 966 1.4× 1.1k 2.5× 436 1.8× 295 1.4× 165 0.9× 98 2.4k
Jennifer L. Gooch United States 28 1.2k 1.7× 398 0.9× 262 1.1× 292 1.4× 34 0.2× 51 2.1k
Tohru Yamazaki Japan 18 702 1.0× 284 0.6× 128 0.5× 213 1.0× 37 0.2× 48 1.7k
Jackie A. Lavigne United States 23 706 1.0× 465 1.1× 351 1.4× 130 0.6× 30 0.2× 28 1.9k
Elisa Petrangeli Italy 27 625 0.9× 277 0.6× 276 1.1× 263 1.3× 47 0.3× 59 1.8k

Countries citing papers authored by Meiru Hu

Since Specialization
Citations

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

Fields of papers citing papers by Meiru Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meiru Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Meiru Hu. A scholar is included among the top collaborators of Meiru Hu 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 Meiru Hu. Meiru Hu 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.
Xu, Huan, et al.. (2020). Autophagic feedback-mediated degradation of IKKα requires CHK1- and p300/CBP-dependent acetylation of p53. Journal of Cell Science. 133(22). 12 indexed citations
2.
Tan, Qixing, Rui Jin, Yongliang Hu, et al.. (2020). Selective degradation of IKKα by autophagy is essential for arsenite-induced cancer cell apoptosis. Cell Death and Disease. 11(4). 222–222. 8 indexed citations
3.
Chen, Changguo, Liang Guo, Ming Shi, et al.. (2012). All-Trans-Retinoic Acid Modulates ICAM-1 N-Glycan Composition by Influencing GnT-III Levels and Inhibits Cell Adhesion and Trans-Endothelial Migration. PLoS ONE. 7(12). e52975–e52975. 16 indexed citations
4.
Liu, Dan, Ming Shi, Hao Zhang, et al.. (2012). c-Myb Regulates Cell Cycle-Dependent Expression of Erbin: An Implication for a Novel Function of Erbin. PLoS ONE. 7(8). e42903–e42903. 6 indexed citations
5.
Chen, Changguo, Liang Guo, Ming Shi, et al.. (2011). Modulation of IFN-γ Receptor 1 Expression by AP-2α Influences IFN-γ Sensitivity of Cancer Cells. American Journal Of Pathology. 180(2). 661–671. 18 indexed citations
6.
Dong, Wen, Yi Li, Ming Gao, et al.. (2011). IKKα contributes to UVB-induced VEGF expression by regulating AP-1 transactivation. Nucleic Acids Research. 40(7). 2940–2955. 37 indexed citations
7.
Li, Yi, Yi Hao, Ming Gao, et al.. (2011). IKKβ downregulation is critical for triggering JNKs-dependent cell apoptotic response in the human hepatoma cells under arsenite exposure. Molecular and Cellular Biochemistry. 358(1-2). 61–66. 3 indexed citations
8.
Shi, Ming, Dan Liu, Huijun Duan, et al.. (2010). The β2-adrenergic receptor and Her2 comprise a positive feedback loop in human breast cancer cells. Breast Cancer Research and Treatment. 125(2). 351–362. 109 indexed citations
9.
Song, Lun, Ming Gao, Wen Dong, et al.. (2010). p85α mediates p53 K370 acetylation by p300 and regulates its promoter-specific transactivity in the cellular UVB response. Oncogene. 30(11). 1360–1371. 27 indexed citations
10.
Shi, Ming, Dan Liu, Huijun Duan, et al.. (2010). Catecholamine up-regulates MMP-7 expression by activating AP-1 and STAT3 in gastric cancer. Molecular Cancer. 9(1). 269–269. 81 indexed citations
11.
Song, Lun, Wen Dong, Ming Gao, et al.. (2010). A novel role of IKKα in the mediation of UVB-induced G0/G1 cell cycle arrest response by suppressing Cyclin D1 expression. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1803(2). 323–332. 15 indexed citations
12.
Li, Dan C., Qian Lü, Changguo Chen, et al.. (2009). Down-Regulation of MHC Class II Expression through Inhibition of CIITA Transcription by Lytic Transactivator Zta during Epstein-Barr Virus Reactivation. The Journal of Immunology. 182(4). 1799–1809. 57 indexed citations
13.
Xia, Qing, Huiping Yan, Qian Lü, et al.. (2008). Serum proteomic-based analysis for the identification of a potential serological marker for autoimmune hepatitis. Biochemical and Biophysical Research Communications. 367(2). 284–290. 9 indexed citations
14.
Lü, Qian, Lun Song, Ming Shi, et al.. (2008). Heregulin-β promotes matrix metalloproteinase-7 expression via HER2-mediated AP-1 activation in MCF-7 cells. Molecular and Cellular Biochemistry. 318(1-2). 73–79. 11 indexed citations
15.
Song, Yuhua, Qian Lu, Santai Song, et al.. (2007). Fra-1 and Stat3 synergistically regulate activation of human MMP-9 gene. Molecular Immunology. 45(1). 137–143. 72 indexed citations
16.
17.
Lü, Qian, Zhiyi Zhang, Ming Shi, et al.. (2006). Expression and distribution of HSP27 in response to G418 in different human breast cancer cell lines. Histochemistry and Cell Biology. 126(5). 593–601. 9 indexed citations
18.
Yang, Zhenhui, Jiannan Feng, Yan Li, et al.. (2004). Structure-based design and characterization of a Novel IL-6 antagonist peptide. Molecular Immunology. 42(9). 1015–1021. 9 indexed citations
19.
Yang, Zhenhui, Jiannan Feng, Meiru Hu, et al.. (2004). A novel hIL-6 antagonist peptide from computer-aided design contributes to suppression of apoptosis in M1 cells. Biochemical and Biophysical Research Communications. 325(2). 518–524. 7 indexed citations
20.
Jin, Baofeng, Kun He, Hongxia Wang, et al.. (2003). Proteomic analysis of ubiquitin-proteasome effects: insight into the function of eukaryotic initiation factor 5A. Oncogene. 22(31). 4819–4830. 59 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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