Mi Mi

467 total citations
12 papers, 327 citations indexed

About

Mi Mi is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Mi Mi has authored 12 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Cancer Research and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Mi Mi's work include Circular RNAs in diseases (4 papers), Cancer-related molecular mechanisms research (4 papers) and Lymphoma Diagnosis and Treatment (3 papers). Mi Mi is often cited by papers focused on Circular RNAs in diseases (4 papers), Cancer-related molecular mechanisms research (4 papers) and Lymphoma Diagnosis and Treatment (3 papers). Mi Mi collaborates with scholars based in China, Israel and Senegal. Mi Mi's co-authors include Zijian Liu, Liling Zhang, Xin Zheng, Xiaoqian Li, Gang Wu, Gang Wu, Xiaomin Zhao, Jianxiong Guo, Xuelian Ma and Dewen Tong and has published in prestigious journals such as Frontiers in Immunology, Medicine and BMC Genomics.

In The Last Decade

Mi Mi

12 papers receiving 323 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mi Mi China 10 192 169 74 69 43 12 327
Beatriz Sánchez‐Sendra Spain 7 297 1.5× 218 1.3× 27 0.4× 67 1.0× 21 0.5× 19 420
Shitong Lin China 15 205 1.1× 120 0.7× 63 0.9× 143 2.1× 28 0.7× 35 466
Mélanie Laporte France 7 100 0.5× 95 0.6× 74 1.0× 112 1.6× 37 0.9× 9 315
Chi Zhu Japan 9 231 1.2× 69 0.4× 18 0.2× 59 0.9× 23 0.5× 10 352
Gongyu Tang United States 6 238 1.2× 97 0.6× 60 0.8× 45 0.7× 17 0.4× 10 322
Gabriela Sofía Gómez-Macias Mexico 8 114 0.6× 111 0.7× 28 0.4× 81 1.2× 39 0.9× 28 260
Esther Yoon United States 9 89 0.5× 46 0.3× 59 0.8× 65 0.9× 31 0.7× 25 235
Munetaka Nakamura Japan 11 86 0.4× 59 0.3× 156 2.1× 251 3.6× 68 1.6× 21 461
Shuyu Xin China 14 298 1.6× 183 1.1× 24 0.3× 153 2.2× 36 0.8× 21 557
Zhihui Dai China 10 373 1.9× 261 1.5× 32 0.4× 40 0.6× 14 0.3× 17 485

Countries citing papers authored by Mi Mi

Since Specialization
Citations

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

Fields of papers citing papers by Mi Mi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mi Mi

This figure shows the co-authorship network connecting the top 25 collaborators of Mi Mi. A scholar is included among the top collaborators of Mi Mi 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 Mi Mi. Mi Mi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Mei, Wei-Jian, et al.. (2022). Clinicopathological characteristics of high microsatellite instability/mismatch repair-deficient colorectal cancer: A narrative review. Frontiers in Immunology. 13. 1019582–1019582. 29 indexed citations
2.
Mi, Mi, Zijian Liu, Xin Zheng, et al.. (2021). Serum metabolomic profiling based on GC/MS helped to discriminate Diffuse Large B-cell Lymphoma patients with different prognosis. Leukemia Research. 111. 106693–106693. 6 indexed citations
3.
4.
Liu, Zijian, Mi Mi, Xin Zheng, et al.. (2021). miR-30a/SOX4 Double Negative Feedback Loop is modulated by Disulfiram and regulates EMT and Stem Cell-like properties in Breast Cancer. Journal of Cancer. 12(16). 5053–5065. 13 indexed citations
5.
6.
Liu, Zijian, Mi Mi, Xiaoqian Li, et al.. (2020). A lncRNA prognostic signature associated with immune infiltration and tumour mutation burden in breast cancer. Journal of Cellular and Molecular Medicine. 24(21). 12444–12456. 83 indexed citations
7.
Li, Xiaoqian, et al.. (2019). <p>Identification of hub genes and key pathways associated with angioimmunoblastic T-cell lymphoma using weighted gene co-expression network analysis</p>. Cancer Management and Research. Volume 11. 5209–5220. 12 indexed citations
8.
Zhao, Xiaomin, Xuelian Ma, Jianxiong Guo, et al.. (2019). Circular RNA CircEZH2 Suppresses Transmissible Gastroenteritis Coronavirus-induced Opening of Mitochondrial Permeability Transition Pore via Targeting MiR-22 in IPEC-J2. International Journal of Biological Sciences. 15(10). 2051–2064. 28 indexed citations
9.
Ma, Xuelian, Xiaomin Zhao, Kaili Wang, et al.. (2019). Identification and analysis of long non-coding RNAs that are involved in inflammatory process in response to transmissible gastroenteritis virus infection. BMC Genomics. 20(1). 806–806. 15 indexed citations
10.
Liu, Zijian, Mi Mi, Xiaoqian Li, et al.. (2019). lncRNA OSTN-AS1 May Represent a Novel Immune-Related Prognostic Marker for Triple-Negative Breast Cancer Based on Integrated Analysis of a ceRNA Network. Frontiers in Genetics. 10. 850–850. 42 indexed citations
11.
Sun, Xun, Juan Li, Zijian Liu, et al.. (2019). Interim PET/CT based on visual and semiquantitative analysis predicts survival in patients with diffuse large B‐cell lymphoma. Cancer Medicine. 8(11). 5012–5022. 23 indexed citations
12.

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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