Ming Qi

131 papers receiving 3.5k citations

Ming Qi's Hit Papers

m6A modification: recent advances, anticancer targeted drug discovery and beyond 2022 · 266 citations
2660+1+2Years since publication50100150200250

Peers

Ming Qi
Comparison fields: 5 of 154
  • Cancer Research 396
  • Cellular and Molecular Neuroscience 426
  • Molecular Biology 1.4k
  • Oncology 471
  • Cardiology and Cardiovascular Medicine 353
Replace Juan Marugán with:
Juan Marugán United States
Kathrin Geiger Germany
Masahiro Yamamoto Japan
Michael Holinstat United States
Mark D. Johnson United States
Katrin Marcus Germany
Pann‐Ghill Suh South Korea
Akira Masuda Japan
Mei Zhao China
Rong Xu China
Ming Qi relative to Juan Marugán United States Juan Marugán's profile →
Citations per field
00.5×2.6×
Juan Marugán · 1×
Citations per year

Countries citing papers authored by Ming Qi

Since Specialization
Citations

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

Fields of papers citing papers by Ming Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming Qi, 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 Ming Qi Line = papers co-authored together Ming Qi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 144 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007317
2
m6A modification: recent advances, anticancer targeted drug discovery and beyond
Hit paper breakdown →
2022266
3 1995233
4 1995191
5 2010190
6 2020156
7 2011139
8 1998129
9 201196
10 201387
11 201870
12 202068
13 202163
14 199863
15 201862
16 202159
17 202350
18 202350
19 201850
20 202149

About Ming Qi

Ming Qi is a scholar working on Molecular Biology, Oncology, Cancer Research, Radiology, Nuclear Medicine and Imaging and Information Systems, having authored 144 papers that have together received 3.5k indexed citations. Recurring topics across this work include Gut microbiota and health (7 papers), Peptidase Inhibition and Analysis (7 papers), MicroRNA in disease regulation (6 papers), Cancer-related molecular mechanisms research (5 papers), Nanoplatforms for cancer theranostics (5 papers), Medical Imaging Techniques and Applications (5 papers), Cardiac electrophysiology and arrhythmias (4 papers) and Neuroscience and Neuropharmacology Research (4 papers). The work is most often cited by research in Cancer Research (396 citations), Cellular and Molecular Neuroscience (426 citations), Molecular Biology (1.4k citations), Oncology (471 citations) and Cardiology and Cardiovascular Medicine (353 citations). Ming Qi has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include G. Stanley McKnight, Rejean L. Idzerda, Lijuan Deng, Dongmei Zhang, Jiaxu Chen, Eugene P. Brandon, Yuhe Lei, Qi Qi, Wen-Yu Lyu and Minfeng Chen. Their work appears in journals such as Journal of Chromatography B, Microbial Pathogenesis, International Immunopharmacology, Journal of Nanobiotechnology and European Journal of Nuclear Medicine and Molecular Imaging.

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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