Ling Zhong

5.6k citations
134 papers · 3.9k indexed · h-index 32
Topics
Neuroscience and Neuropharmacology Research (10 papers)Traditional Chinese Medicine Analysis (9 papers)Ion channel regulation and function (7 papers)

In The Last Decade

Ling Zhong

124 papers receiving 3.9k citations

Peers

Ling Zhong
Comparison fields: 5 of 148
  • Molecular Biology 1.8k
  • Physiology 465
  • Epidemiology 433
  • Immunology 343
  • Ecology 315
Replace Angela Amoresano with:
Angela Amoresano Italy
Qí Zhāng China
Kenji Sato Japan
Won Sun Park South Korea
Anil Kumar Verma India
Ji‐Eun Kim South Korea
Michael E. Maguire United States
Yanli Liu China
Yuan Zhang China
Ling Zhong relative to Angela Amoresano Italy Angela Amoresano's profile →
Citations per field
00.5×2.7×
Angela Amoresano · 1×
Citations per year

Countries citing papers authored by Ling Zhong

Since Specialization
Citations

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

Fields of papers citing papers by Ling Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Zhong

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Zhong. A scholar is included among the top collaborators of Ling Zhong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ling Zhong. Ling Zhong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 13
3 17
4 0
5 4
6 0
7 0
8 30
9 29
10 2
11 15
12 8
13 13
14 12
15 31
16 9
17 56
18
Combination of methotrexate and mifepristone versus methotrexate alone for patients with ectopic pregnancy:a systematic review
1
19 58
20 67

About Ling Zhong

Ling Zhong is a scholar working on Structural Biology, Complementary and alternative medicine and Developmental Neuroscience, having authored 134 papers that have together received 3.9k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (10 papers), Traditional Chinese Medicine Analysis (9 papers) and Ion channel regulation and function (7 papers). The work is most often cited by research in Molecular Biology (1.8k citations), Microbiology (154 citations) and Sensory Systems (100 citations). Ling Zhong has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Mark J. Raftery, Nashaat Z. Gerges, Aimin Xu, Lutfi Abu-Elheiga, Gebretateos Woldegiorgis, Salih J. Wakil, William R. Brinkley, Subrahmanyam S. Chirala, Yu Wang and Ricardo Cavicchioli. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Advanced Materials.

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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