Dan Liao

537 citations
11 papers · 416 indexed · 2 hit papers · h-index 7
Topics
Biosensors and Analytical Detection (4 papers)Advanced biosensing and bioanalysis techniques (4 papers)CRISPR and Genetic Engineering (3 papers)
Partner nations
ChinaUnited Kingdom

In The Last Decade

Dan Liao

10 papers receiving 415 citations

Hit Papers

Novel non-nucleic acid targets detection strategies based...2022202620232024202220244080120

Peers

Dan Liao
Comparison fields: 5 of 53
  • Molecular Biology 349
  • Biomedical Engineering 186
  • Materials Chemistry 40
  • Cancer Research 38
  • Ecology 24
Replace Jun Kou with:
Jun Kou China
Shaohua Gong China
Dongjuan Chen China
Xiaoxue Cheng China
Yao Yin China
Fangqi Peng China
Guan A. Wang China
Yin Tan Singapore
Fangfang Zhan China
Dan Liao relative to Jun Kou China Jun Kou's profile →
Citations per field
00.5×3.8×
Jun Kou · 1×
Citations per year

Countries citing papers authored by Dan Liao

Since Specialization
Citations

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

Fields of papers citing papers by Dan Liao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Liao

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Liao. A scholar is included among the top collaborators of Dan Liao 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 Dan Liao. Dan Liao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
#WorkIndexed citations
1 6
2 0
3 2
4
A feedback loop driven by H3K9 lactylation and HDAC2 in endothelial cells regulates VEGF-induced angiogenesisbreakdown →
59
5 47
6 79
7
Novel non-nucleic acid targets detection strategies based on CRISPR/Cas toolboxes: A reviewbreakdown →
149
8 58
9 2
10 5
11 9

About Dan Liao

Dan Liao is a scholar working on Obstetrics and Gynecology, Cancer Research and Biomedical Engineering, having authored 11 papers that have together received 416 indexed citations. Recurring topics across this work include Biosensors and Analytical Detection (4 papers), Advanced biosensing and bioanalysis techniques (4 papers) and CRISPR and Genetic Engineering (3 papers). The work is most often cited by research in Business and International Management (18 citations), Molecular Biology (349 citations) and Biomedical Engineering (186 citations). Dan Liao has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Shuli Man, Long Ma, Yaru Li, Jun Kou, Wenlu Zhang, Lijuan Yin, Junling Wang, Xiao Han, Yigang Tong and Xin Xiong. Their work appears in journals such as Journal of Hazardous Materials, Genome biology and Trends in biotechnology.

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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