Hui Jin

50 papers receiving 1.2k citations

Peers

Hui Jin
Comparison fields: 5 of 119
  • Aging 85
  • Cellular and Molecular Neuroscience 246
  • Ophthalmology 84
  • Molecular Biology 681
  • Cell Biology 144
Replace Satoshi Tsukamoto with:
Satoshi Tsukamoto Japan
Seiji Takagi Japan
Ryan K. C. Yuen Canada
Yusuke Takeuchi Japan
Samantha J. Riesenfeld United States
Dirk L. Ypey Netherlands
Tal Mizrahi Israel
Boxun Lu China
N. Nagai Japan
Hui Jin relative to Satoshi Tsukamoto Japan Satoshi Tsukamoto's profile →
Citations per field
00.5×4.4×
Satoshi Tsukamoto · 1×
Citations per year

Countries citing papers authored by Hui Jin

Since Specialization
Citations

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

Fields of papers citing papers by Hui Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996190
2 2004122
3 2002106
4 201570
5 201169
6 201869
7 200268
8 201853
9 200753
10 200251
11 201547
12 201236
13 201631
14 202127
15 201126
16 200526
17 201923
18 201621
19 201117
20 200617

About Hui Jin

Hui Jin is a scholar working on Molecular Biology, Electrical and Electronic Engineering, Computer Networks and Communications, Cellular and Molecular Neuroscience and Surgery, having authored 51 papers that have together received 1.3k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (10 papers), Advanced Wireless Communication Techniques (9 papers), Retinal Development and Disorders (8 papers), Photoreceptor and optogenetics research (6 papers), Error Correcting Code Techniques (5 papers), Cooperative Communication and Network Coding (4 papers), Neurobiology and Insect Physiology Research (3 papers) and Geotechnical Engineering and Underground Structures (3 papers). The work is most often cited by research in Aging (85 citations), Cellular and Molecular Neuroscience (246 citations), Ophthalmology (84 citations), Molecular Biology (681 citations) and Cell Biology (144 citations). Hui Jin has collaborated with scholars based in United States, China and Belgium. Frequent co-authors include Jack L. Lewis, Krzysztof Palczewski, Robert J. McEliece, Vern Twombly, Ronald K. Blackman, Jonathan M. Graff, William M Gelbart, Richard W. Padgett, Tanya Richardson and Beata Jastrzębska. Their work appears in journals such as The FASEB Journal, International Journal of Critical Infrastructures, Investigative Ophthalmology & Visual Science, Nature Communications and Journal of Biomechanical Engineering.

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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