Ting Mu

757 citations
20 papers · 298 · h-index 8

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Hepatitis C virus research

Papers in

Ting Mu

20 papers receiving 296 citations

Peers

Ting Mu
Comparison fields: 5 of 62
  • Cancer Research 88
  • Hepatology 38
  • Immunology 46
  • Epidemiology 68
  • Molecular Biology 134
Replace S S Gong with:
S S Gong United States
Kay Osborn United Kingdom
Vassiliki Stamatopoulou Greece
Bipin C. Dash United States
Sanqi An China
Philippe Neuner Italy
Lakshmi Gopinathan United States
Joshua R. Leeman United States
Marcus R. Kelly United States
Daowei Yang China
Ting Mu relative to S S Gong United States S S Gong's profile →
Citations per field
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S S Gong · 1×
Citations per year

Countries citing papers authored by Ting Mu

Since Specialization
Citations

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

Fields of papers citing papers by Ting Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ting Mu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ting Mu Line = papers co-authored together Ting Mu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201972
2 201860
3 202046
4 202031
5 201926
6 201616
7 202010
8 20199
9 20225
10
A Theoretical Study on the Stereoisomerism in the Complex of Cucurbit[8]uril with 2, 6-Bis(4, 5-dihydro-1H-imidazol-2-yl)naphthalene
20015
11 20234
12 20223
13 20083
14 20202
15 20231
16 20241
17 20081
18
A Molecular Modeling for the Complexation of Cyclobis(paraquat-p-phenylene) with Substituted Benzenes and Biphenyls
20001
19 20251
20 20211

About Ting Mu

Ting Mu is a scholar working on Molecular Biology, Epidemiology, Organic Chemistry, Cancer Research and Materials Chemistry, having authored 20 papers that have together received 298 indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (3 papers), Carbon and Quantum Dots Applications (3 papers), Circular RNAs in diseases (2 papers), Dendrimers and Hyperbranched Polymers (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), MicroRNA in disease regulation (2 papers), RNA modifications and cancer (2 papers) and Algebraic structures and combinatorial models (1 paper). The work is most often cited by research in Cancer Research (88 citations), Hepatology (38 citations), Immunology (46 citations), Epidemiology (68 citations) and Molecular Biology (134 citations). Ting Mu has collaborated with scholars based in China, United States and Philippines. Frequent co-authors include Hua Tang, Hongxia Fan, Hong Xie, Min Liu, Yanan Zhu, Lu Sun, Chaoqun Ma, Xiaoqing Zhao, Xiaoqing Zhao and Yankun Liu. Their work appears in journals such as Vaccines, Cancer Letters, Frontiers in Cellular and Infection Microbiology, Journal of Assisted Reproduction and Genetics and Journal of Cancer.

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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