Lingyun Dai

3.0k citations
72 papers · 2.0k indexed · 1 hit paper · h-index 24
Topics
Computational Drug Discovery Methods (10 papers)Ubiquitin and proteasome pathways (5 papers)Advanced Proteomics Techniques and Applications (5 papers)
Partner nations
ChinaSingaporeSweden

In The Last Decade

Lingyun Dai

63 papers receiving 2.0k citations

Hit Papers

Celastrol induces ferroptosis in activated HSCs to amelio...2021202620222024202150100150200

Peers

Lingyun Dai
Comparison fields: 5 of 112
  • Molecular Biology 1.3k
  • Cancer Research 408
  • Immunology 241
  • Oncology 215
  • Pulmonary and Respiratory Medicine 210
Replace Raymond Wu with:
Raymond Wu United States
Brett Lomenick United States
Monica Schenone United States
Xianzhang Bu China
Sudhir Srivastava United States
Yongliang Yang China
Peh Yean Cheah Singapore
Sara J. Buhrlage United States
Philip L. Lorenzi United States
Lingyun Dai relative to Raymond Wu United States Raymond Wu's profile →
Citations per field
00.5×3.0×
Raymond Wu · 1×
Citations per year

Countries citing papers authored by Lingyun Dai

Since Specialization
Citations

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

Fields of papers citing papers by Lingyun Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingyun Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Lingyun Dai. A scholar is included among the top collaborators of Lingyun 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 Lingyun Dai. Lingyun 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 1
2 4
3 0
4 4
5 0
6 6
7 5
8 2
9 4
10 4
11 11
12 27
13 72
14 22
15
Celastrol induces ferroptosis in activated HSCs to ameliorate hepatic fibrosis via targeting peroxiredoxins and HO-1breakdown →
233
16 77
17 152
18 41
19
Establishment of ISSR-PCR reaction system of Idesia polycarpa and the screening of primers
2
20 41

About Lingyun Dai

Lingyun Dai is a scholar working on Microbiology, Computational Theory and Mathematics and Cancer Research, having authored 72 papers that have together received 2.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Ubiquitin and proteasome pathways (5 papers) and Advanced Proteomics Techniques and Applications (5 papers). The work is most often cited by research in Cancer Research (408 citations), Molecular Biology (1.3k citations) and Computational Theory and Mathematics (199 citations). Lingyun Dai has collaborated with scholars based in China, Singapore and Sweden. Frequent co-authors include P. Nordlund, Nayana Prabhu, Jigang Wang, Radoslaw M. Sobota, Zhijie Li, Yan Ting Lim, Chuanbin Yang, Piao Luo, Junzhe Zhang and Fan Yang. Their work appears in journals such as Science, Cell 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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