Mu‐Shui Dai

4.9k citations
62 papers · 3.6k indexed · 1 hit paper · h-index 30
Topics
Cancer-related Molecular Pathways (27 papers)Ubiquitin and proteasome pathways (25 papers)RNA modifications and cancer (21 papers)
Partner nations
United StatesChinaJapan

In The Last Decade

Mu‐Shui Dai

61 papers receiving 3.6k citations

Hit Papers

Identifying phenotype-associated subpopulations by integr...2021202620222024202150100150200

Peers

Mu‐Shui Dai
Comparison fields: 5 of 102
  • Molecular Biology 3.1k
  • Oncology 1.5k
  • Cancer Research 656
  • Immunology 301
  • Cell Biology 240
Replace David Dornan with:
David Dornan United States
Daniel J. Murphy United Kingdom
Karsten Zieger Denmark
Álvaro J. Obaya Spain
Gareth L. Bond United Kingdom
Torben F. Ørntoft Denmark
Mark A. Subler United States
Licio Collavin Italy
Simona Ronzoni Italy
Mark K. Saville United Kingdom
Mu‐Shui Dai relative to David Dornan United States David Dornan's profile →
Citations per field
00.5×3.8×
David Dornan · 1×
Citations per year

Countries citing papers authored by Mu‐Shui Dai

Since Specialization
Citations

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

Fields of papers citing papers by Mu‐Shui Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mu‐Shui Dai. 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 Mu‐Shui Dai. The network helps show where Mu‐Shui Dai may publish in the future.

Co-authorship network of co-authors of Mu‐Shui Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Mu‐Shui Dai. A scholar is included among the top collaborators of Mu‐Shui Dai 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 Mu‐Shui Dai. Mu‐Shui Dai 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 14
2 13
3 7
4
Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing databreakdown →
234
5 31
6 47
7 45
8 54
9 7
10 10
11 1
12 171
13 43
14 16
15 87
16 102
17 409
18 7
19 16
20 4

About Mu‐Shui Dai

Mu‐Shui Dai is a scholar working on Oncology, Cancer Research and Molecular Biology, having authored 62 papers that have together received 3.6k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (27 papers), Ubiquitin and proteasome pathways (25 papers) and RNA modifications and cancer (21 papers). The work is most often cited by research in Oncology (1.5k citations), Molecular Biology (3.1k citations) and Cancer Research (656 citations). Mu‐Shui Dai has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Hua Lu, Xiao‐Xin Sun, Rosalie C. Sears, Yetao Jin, Kishore B. Challagundla, Shelya X. Zeng, Larry L. David, David Z. Qian, Xia He and Yingxiao Chen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research 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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