Ke Ning

6.0k citations
114 papers · 4.4k · h-index 37

Impact in

Papers in

    • RNA modifications and cancer 10
    • Cell death mechanisms and regulation 7
    • RNA Interference and Gene Delivery 6
    • RNA Research and Splicing 6
    • 3D Printing in Biomedical Research 11

Ke Ning

108 papers receiving 4.3k citations

Peers

Ke Ning
Comparison fields: 5 of 147
  • Genetics 652
  • Cellular and Molecular Neuroscience 729
  • Molecular Biology 2.5k
  • Developmental Neuroscience 114
  • Endocrine and Autonomic Systems 174
Replace Marı́a T. Berciano with:
Marı́a T. Berciano Spain
Miguel Lafarga Spain
Donald R. Love New Zealand
Alessandro Quattrone Italy
Daniel F. Schorderet Switzerland
Masuo Obinata Japan
Lin Gao China
Mathias Hafner Germany
Mario Molinaro Italy
Dongmei Cheng United States
Ke Ning relative to Marı́a T. Berciano Spain Marı́a T. Berciano's profile →
Citations per field
00.5×1.5×2.1×
Marı́a T. Berciano · 1×
Citations per year

Countries citing papers authored by Ke Ning

Since Specialization
Citations

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

Fields of papers citing papers by Ke Ning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011333
2 2004242
3 2010225
4 2003157
5 2006154
6 1996151
7 2004149
8 2004144
9 2012119
10 2008118
11 2002112
12 2004107
13 2010106
14 2001105
15 200297
16 200684
17 200082
18 201780
19 200073
20 199672

About Ke Ning

Ke Ning is a scholar working on Molecular Biology, Biomedical Engineering, Genetics, Cellular and Molecular Neuroscience and Plant Science, having authored 114 papers that have together received 4.4k indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (11 papers), Neurogenetic and Muscular Disorders Research (11 papers), RNA modifications and cancer (10 papers), Neurogenesis and neuroplasticity mechanisms (7 papers), Amyotrophic Lateral Sclerosis Research (7 papers), Cell death mechanisms and regulation (7 papers), RNA Interference and Gene Delivery (6 papers) and RNA Research and Splicing (6 papers). The work is most often cited by research in Genetics (652 citations), Cellular and Molecular Neuroscience (729 citations), Molecular Biology (2.5k citations), Developmental Neuroscience (114 citations) and Endocrine and Autonomic Systems (174 citations). Ke Ning has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include John C. Reed, Yama Abassi, Daniel F. Voytas, Xiao Yun Xu, Adam Godzik, Xiaobo Wang, Pamela J. Shaw, Mimoun Azzouz, Chiara F. Valori and Matthew Wyles. Their work appears in journals such as Cell Death and Disease, Journal of Biological Chemistry, Sensors and Actuators B Chemical, RNA and Experimental Cell Research.

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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