Ming Sheng

802 citations
22 papers · 385 · h-index 10

Impact in

Papers in

Ming Sheng

18 papers receiving 380 citations

Peers

Ming Sheng
Comparison fields: 5 of 99
  • Aging 104
  • Biological Psychiatry 28
  • Endocrine and Autonomic Systems 37
  • Health Information Management 24
  • Cell Biology 63
Replace Habil Zare with:
Habil Zare United States
Sipko van Dam Netherlands
Mary Shimoyama United States
Peipei Ping United States
Bruno César Feltes Brazil
Uday S. Evani United States
Serdar Bozdag United States
Jiahao Huang United States
Matthew Simon United States
Yulin Dai United States
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Citations per field
00.5×3.4×
Habil Zare · 1×
Citations per year

Countries citing papers authored by Ming Sheng

Since Specialization
Citations

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

Fields of papers citing papers by Ming Sheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201793
2 201979
3 202056
4 202035
5 202028
6 201519
7 202218
8 201518
9 201611
10 20179
11 20235
12 20243
13
[Bioinformatics-based identification of the key genes associated with prostate cancer].
20213
14 20242
15
[Inhibition of angiogenesis properties by SZ-21].
20032
16 20161
17
[Proliferation inhibition of human lung adenocarcinoma cell line A549 transfected by RASSF1A gene].
20051
18 20251
19 20251
20 20250

About Ming Sheng

Ming Sheng is a scholar working on Aging, Endocrine and Autonomic Systems, Cell Biology, Molecular Biology and Health Information Management, having authored 22 papers that have together received 385 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (5 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Circadian rhythm and melatonin (3 papers), Data Quality and Management (2 papers), Artificial Intelligence in Healthcare (2 papers), Head and Neck Cancer Studies (1 paper), Infrastructure Maintenance and Monitoring (1 paper) and Cellular transport and secretion (1 paper). The work is most often cited by research in Aging (104 citations), Biological Psychiatry (28 citations), Endocrine and Autonomic Systems (37 citations), Health Information Management (24 citations) and Cell Biology (63 citations). Ming Sheng has collaborated with scholars based in China, United Kingdom and Australia. Frequent co-authors include Rebecca C. Taylor, Julian L. Griffin, Cecilia Castro, Yong Zhang, Rui Zhou, Eisuke Itakura, Patrick Laurent, Lorenz A. Fenk, Ramanujan S. Hegde and Changchun Chen. Their work appears in journals such as Health Information Science and Systems, Information Processing & Management, Developmental Cell, Cell Reports and PLoS ONE.

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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