Kun Huang

3.2k citations
53 papers · 2.5k · h-index 20

Impact in

Papers in

Kun Huang

50 papers receiving 2.4k citations

Peers

Kun Huang
Comparison fields: 5 of 108
  • Cellular and Molecular Neuroscience 1.0k
  • Cell Biology 607
  • Developmental Neuroscience 107
  • Molecular Biology 1.5k
  • Neurology 146
Replace Gail M. Seigel with:
Gail M. Seigel United States
Daniele Zacchetti Italy
James M. Angelastro United States
M Bossi Italy
Michel J. Roux France
Franca Codazzi Italy
Paul S. Amieux United States
Carsten Jäger Germany
Richard Rivera United States
Fumitoshi Irie Japan
Kun Huang relative to Gail M. Seigel United States Gail M. Seigel's profile →
Citations per field
00.5×1.5×2.4×
Gail M. Seigel · 1×
Citations per year

Countries citing papers authored by Kun Huang

Since Specialization
Citations

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

Fields of papers citing papers by Kun Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008450
2 2004258
3 2006246
4 2005219
5 2009129
6 2010128
7 2017124
8 2005115
9 201193
10 200893
11 201083
12 201171
13 201965
14 200844
15 201543
16 202030
17 201824
18 201124
19 201220
20 201819

About Kun Huang

Kun Huang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Epidemiology, Pulmonary and Respiratory Medicine and Rheumatology, having authored 53 papers that have together received 2.5k indexed citations. Recurring topics across this work include Inflammatory Myopathies and Dermatomyositis (9 papers), Eosinophilic Disorders and Syndromes (7 papers), Neuroscience and Neuropharmacology Research (7 papers), Genetic Neurodegenerative Diseases (7 papers), Mitochondrial Function and Pathology (6 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (5 papers), Muscle Physiology and Disorders (5 papers) and HIV/AIDS Research and Interventions (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.0k citations), Cell Biology (607 citations), Developmental Neuroscience (107 citations), Molecular Biology (1.5k citations) and Neurology (146 citations). Kun Huang has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Alaa El‐Husseini, Rujun Kang, Pamela Arstikaitis, Michael R. Hayden, Roshni R. Singaraja, Alaa El-Husseini, Junmei Wan, Renaldo C. Drisdel, Anat Yanai and William N. Green. Their work appears in journals such as Lara D. Veeken, Journal of Biological Chemistry, PLoS ONE, Human Molecular Genetics and Seminars in Arthritis and Rheumatism.

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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