Jeffrey K. Huang

3.9k citations
58 papers · 3.0k indexed · h-index 25

Jeffrey K. Huang

56 papers receiving 2.9k citations

Peers

Jeffrey K. Huang
Comparison fields: 5 of 114
  • Developmental Neuroscience 1.1k
  • Neurology 659
  • Cellular and Molecular Neuroscience 949
  • Pathology and Forensic Medicine 484
  • Biological Psychiatry 64
Replace Corinna Lappe-Siefke with:
Corinna Lappe-Siefke Germany
Simone Di Giovanni Germany
Judith B. Grinspan United States
Peter Bannerman United States
Julia M. Edgar United Kingdom
Johannes Vogt Germany
Sjef Copray Netherlands
Xinghua Yin United States
Patrick Küry Germany
Steven Petratos Australia
Jeffrey K. Huang relative to Corinna Lappe-Siefke Germany Corinna Lappe-Siefke's profile →
Citations per field
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Corinna Lappe-Siefke · 1×
Citations per year

Countries citing papers authored by Jeffrey K. Huang

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey K. Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20254
2 20242
3 20238
4 20232
5 202310
6 20226
7 202111
8 201737
9 201613
10 201564
11 201217
12 201142
13 201138
14 2010423
15 2010136
16 200723
17 20052
18 200119
19 2001354
20 19994

About Jeffrey K. Huang

Jeffrey K. Huang is a scholar working on Developmental Neuroscience, Neurology and Cellular and Molecular Neuroscience, having authored 58 papers that have together received 3.0k indexed citations. Recurring topics across this work include Neurogenesis and neuroplasticity mechanisms (26 papers), Neuroinflammation and Neurodegeneration Mechanisms (17 papers), Multiple Sclerosis Research Studies (9 papers), Nerve injury and regeneration (9 papers), Retinoids in leukemia and cellular processes (5 papers), Axon Guidance and Neuronal Signaling (4 papers), Hereditary Neurological Disorders (3 papers) and RNA Research and Splicing (3 papers). The work is most often cited by research in Developmental Neuroscience (1.1k citations), Neurology (659 citations) and Cellular and Molecular Neuroscience (949 citations). Jeffrey K. Huang has collaborated with scholars based in United States, United Kingdom and Taiwan. Frequent co-authors include David Colman, Robin J.M. Franklin, Liliana Pedraza, Chao Zhao, Christophe Kerninon, Charles ffrench‐Constant, Catherine Lubetzki, Brahim Nait‐Oumesmar, Andrew A. Jarjour and Weisong Shan. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

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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