Shaoping Ji

3k citations
91 papers · 2.5k · h-index 24

Impact in

Papers in

Shaoping Ji

86 papers receiving 2.5k citations

Peers

Shaoping Ji
Comparison fields: 5 of 107
  • Developmental Neuroscience 70
  • Cancer Research 295
  • Molecular Biology 1.1k
  • Aging 26
  • Geriatrics and Gerontology 56
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Daniela Volonté United States
Claudia Colussi Italy
Qingyuan Ge United States
Keyong Du United States
Stephen R. Johnstone United Kingdom
Dorothea Rudolph Austria
Jean‐Sébastien Annicotte France
Yongjun Fan United States
Christopher L. Antos Germany
Vincent Paupe United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Shaoping Ji

Since Specialization
Citations

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

Fields of papers citing papers by Shaoping Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Circular RNAs as potential biomarkers for cancer diagnosis and therapy.
2016228
2 2016197
3 2003194
4 2018168
5 2017140
6 2006129
7 201599
8 200888
9 200681
10 200876
11 201170
12 202263
13 200548
14 202044
15 201742
16 200840
17 202235
18 202033
19 201532
20 202131

About Shaoping Ji

Shaoping Ji is a scholar working on Molecular Biology, Developmental Neuroscience, Cancer Research, Geriatrics and Gerontology and Oncology, having authored 91 papers that have together received 2.5k indexed citations. Recurring topics across this work include Neurogenesis and neuroplasticity mechanisms (7 papers), RNA Research and Splicing (6 papers), Cancer-related molecular mechanisms research (6 papers), Nanoparticles: synthesis and applications (5 papers), Gene expression and cancer classification (4 papers), Epigenetics and DNA Methylation (4 papers), Cancer-related Molecular Pathways (4 papers) and Sirtuins and Resveratrol in Medicine (4 papers). The work is most often cited by research in Developmental Neuroscience (70 citations), Cancer Research (295 citations), Molecular Biology (1.1k citations), Aging (26 citations) and Geriatrics and Gerontology (56 citations). Shaoping Ji has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Wenqiang Wei, Adil J. Nazarali, Fengling Wang, Yang An, Kendra L. Furber, Xiangqian Guo, Xin‐Ying Ji, Xinping Liu, Libo Yao and Hua Han. Their work appears in journals such as Frontiers in Oncology, International Journal of Nanomedicine, International Journal of Molecular Sciences, Journal of Cellular and Molecular Medicine and Frontiers in Molecular Biosciences.

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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