Ka Young Chung

6.1k citations
82 papers · 4.5k indexed · 2 hit papers · h-index 23
Topics
Receptor Mechanisms and Signaling (56 papers)Protein Kinase Regulation and GTPase Signaling (22 papers)Neuropeptides and Animal Physiology (20 papers)

In The Last Decade

Ka Young Chung

79 papers receiving 4.5k citations

Hit Papers

Crystal structure of the β2 adrenergic receptor–Gs protei...20112026201620212011201150010001.5k2.0k

Peers

Ka Young Chung
Comparison fields: 5 of 109
  • Molecular Biology 4.1k
  • Cellular and Molecular Neuroscience 2.1k
  • Radiology, Nuclear Medicine and Imaging 604
  • Spectroscopy 534
  • Computational Theory and Mathematics 362
Replace Joseph A. Lyons with:
Joseph A. Lyons Denmark
Yaozhong Zou United States
Jesper Mosolff Mathiesen Denmark
Brian T. DeVree United States
Naomi R. Latorraca United States
Diane Calinski United States
Daniel Wacker United States
Daniel H. Arlow United States
Xavier Deupí Switzerland
Matthieu Masureel United States
Ka Young Chung relative to Joseph A. Lyons Denmark Joseph A. Lyons's profile →
Citations per field
00.5×1.5×
Joseph A. Lyons · 1×
Citations per year

Countries citing papers authored by Ka Young Chung

Since Specialization
Citations

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

Fields of papers citing papers by Ka Young Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ka Young Chung. 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 Ka Young Chung. The network helps show where Ka Young Chung may publish in the future.

Co-authorship network of co-authors of Ka Young Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Ka Young Chung. A scholar is included among the top collaborators of Ka Young Chung 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 Ka Young Chung. Ka Young Chung 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 1
2 1
3 3
4 2
5 15
6 6
7 4
8 38
9 8
10 47
11 18
12 19
13 69
14 13
15 0
16 7
17 16
18 13
19
Conformational changes in the G protein Gs induced by the β2 adrenergic receptorbreakdown →
290
20 9

About Ka Young Chung

Ka Young Chung is a scholar working on Cellular and Molecular Neuroscience, Spectroscopy and Molecular Biology, having authored 82 papers that have together received 4.5k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (56 papers), Protein Kinase Regulation and GTPase Signaling (22 papers) and Neuropeptides and Animal Physiology (20 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (2.1k citations), Molecular Biology (4.1k citations) and Spectroscopy (534 citations). Ka Young Chung has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Brian K. Kobilka, Søren G. F. Rasmussen, Roger K. Sunahara, Diane Calinski, Brian T. DeVree, Pil Seok Chae, Georgios Skiniotis, Jan Steyaert, Els Pardon and Andrew C. Kruse. Their work appears in journals such as Nature, Science and Cell.

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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