Lian Cen

4.4k total citations · 1 hit paper
85 papers, 3.6k citations indexed

About

Lian Cen is a scholar working on Biomedical Engineering, Biomaterials and Surgery. According to data from OpenAlex, Lian Cen has authored 85 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Biomedical Engineering, 35 papers in Biomaterials and 18 papers in Surgery. Recurrent topics in Lian Cen's work include Electrospun Nanofibers in Biomedical Applications (20 papers), Bone Tissue Engineering Materials (16 papers) and Tissue Engineering and Regenerative Medicine (11 papers). Lian Cen is often cited by papers focused on Electrospun Nanofibers in Biomedical Applications (20 papers), Bone Tissue Engineering Materials (16 papers) and Tissue Engineering and Regenerative Medicine (11 papers). Lian Cen collaborates with scholars based in China, Singapore and United Kingdom. Lian Cen's co-authors include K. G. Neoh, E. T. Kang, Lei Cui, Yilin Cao, Wei Liu, Wenjie Zhang, Shuo Yin, Guangpeng Liu, Qihai Liu and Yali Li and has published in prestigious journals such as Advanced Materials, Biomaterials and Advanced Functional Materials.

In The Last Decade

Lian Cen

82 papers receiving 3.6k citations

Hit Papers

Collagen Tissue Engineering: Development of Novel Biomate... 2008 2026 2014 2020 2008 100 200 300 400 500

Peers

Lian Cen
Comparison fields: 5 of 131
  • Biomedical Engineering 1.6k
  • Biomaterials 1.4k
  • Surgery 899
  • Molecular Biology 509
  • Genetics 428
Replace Jennifer H. Elisseeff with:
Jennifer H. Elisseeff United States
Sun‐Woong Kang South Korea
Cleo Choong Singapore
Lie Ma China
Qian Feng China
Anna Finne‐Wistrand Sweden
Jörg Teßmar Germany
Huanan Wang China
Shahin Bonakdar Iran
Heidi Declercq Belgium
Jennifer H. Elisseeff United States View profile →
Citations per field, relative to Lian Cen
Lian Cen · 1×
Citations per year, relative to Lian Cen
Lian Cen · 1×

Countries citing papers authored by Lian Cen

Since Specialization
Citations

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

Fields of papers citing papers by Lian Cen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lian Cen

This figure shows the co-authorship network connecting the top 25 collaborators of Lian Cen. A scholar is included among the top collaborators of Lian Cen 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 Lian Cen. Lian Cen 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
# Work Indexed citations
1 1
2 0
3 1
4 0
5 1
6 4
7 8
8 5
9 2
10 25
11 50
12 5
13 22
14 26
15 43
16 144
17 44
18 95
19 30
20 212

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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