Chun‐wa Chung

12.0k citations
76 papers · 4.3k indexed · 1 hit paper · h-index 32
Topics
Protein Degradation and Inhibitors (40 papers)Multiple Myeloma Research and Treatments (22 papers)Ubiquitin and proteasome pathways (21 papers)

In The Last Decade

Chun‐wa Chung

76 papers receiving 4.2k citations

Hit Papers

Suppression of inflammation by a synthetic histone mimic201020262015202020104008001.2k

Peers

Chun‐wa Chung
Comparison fields: 5 of 122
  • Molecular Biology 3.4k
  • Hematology 997
  • Oncology 735
  • Organic Chemistry 538
  • Immunology 489
Replace O. Fedorov with:
O. Fedorov United Kingdom
P. Filippakopoulos United Kingdom
Brian D. Marsden United Kingdom
John H. Bushweller United States
Tomasz Cierpicki United States
Keith P. Wilson United States
F. von Delft United Kingdom
Markus A. Seeliger United States
Luciana Marinelli Italy
Paul E. Brennan United Kingdom
Chun‐wa Chung relative to O. Fedorov United Kingdom O. Fedorov's profile →
Citations per field
00.5×2.8×
O. Fedorov · 1×
Citations per year

Countries citing papers authored by Chun‐wa Chung

Since Specialization
Citations

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

Fields of papers citing papers by Chun‐wa Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun‐wa 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 Chun‐wa Chung. The network helps show where Chun‐wa Chung may publish in the future.

Co-authorship network of co-authors of Chun‐wa Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Chun‐wa Chung. A scholar is included among the top collaborators of Chun‐wa 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 Chun‐wa Chung. Chun‐wa 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 7
2 6
3 5
4 85
5 4
6 18
7 67
8 32
9 17
10 24
11 12
12 14
13 45
14 23
15 37
16 25
17 68
18 37
19 26
20 11

About Chun‐wa Chung

Chun‐wa Chung is a scholar working on Hematology, Structural Biology and Molecular Biology, having authored 76 papers that have together received 4.3k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (40 papers), Multiple Myeloma Research and Treatments (22 papers) and Ubiquitin and proteasome pathways (21 papers). The work is most often cited by research in Hematology (997 citations), Molecular Biology (3.4k citations) and Virology (153 citations). Chun‐wa Chung has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Rab K. Prinjha, Paul Bamborough, Uwe Schaefer, Alexander Tarakhovsky, Edwige Nicodème, Rohit Chandwani, Kate L. Jeffrey, Jorge Kirilovsky, Julia H. White and Charles M. Rice. Their work appears in journals such as Nature, Journal of the American Chemical Society and Journal of Biological Chemistry.

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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