Ian Lian

3.9k total citations · 3 hit papers
30 papers, 3.1k citations indexed

About

Ian Lian is a scholar working on Molecular Biology, Biomedical Engineering and Mechanics of Materials. According to data from OpenAlex, Ian Lian has authored 30 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Biomedical Engineering and 8 papers in Mechanics of Materials. Recurrent topics in Ian Lian's work include Surface Modification and Superhydrophobicity (8 papers), Metal and Thin Film Mechanics (4 papers) and Cellular Mechanics and Interactions (4 papers). Ian Lian is often cited by papers focused on Surface Modification and Superhydrophobicity (8 papers), Metal and Thin Film Mechanics (4 papers) and Cellular Mechanics and Interactions (4 papers). Ian Lian collaborates with scholars based in United States, China and Taiwan. Ian Lian's co-authors include Kun‐Liang Guan, Bin Zhao, Jiagang Zhao, Fa‐Xing Yu, Hairi Li, Xiang‐Dong Fu, Karen Tumaneng, Jenna L. Jewell, Nattapon Panupinthu and Hai‐Xin Yuan and has published in prestigious journals such as Nature, Cell and Circulation.

In The Last Decade

Ian Lian

29 papers receiving 3.1k citations

Hit Papers

Regulation of the Hippo-YAP Pathway by G-Protein-Coupled ... 2010 2026 2015 2020 2012 2010 2015 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ian Lian United States 16 1.8k 1.8k 342 226 202 30 3.1k
Megan M. Young United States 26 489 0.3× 1.2k 0.7× 153 0.4× 245 1.1× 262 1.3× 41 2.4k
Stuart T. Fraser Australia 32 656 0.4× 1.4k 0.8× 167 0.5× 154 0.7× 457 2.3× 92 2.8k
Daniel E. Conway United States 23 1.1k 0.6× 1.1k 0.6× 165 0.5× 392 1.7× 152 0.8× 54 2.4k
Beata Wójciak‐Stothard United Kingdom 30 1.0k 0.6× 2.1k 1.2× 243 0.7× 624 2.8× 630 3.1× 55 4.5k
J. M. Vasiliev Russia 33 1.6k 0.9× 1.2k 0.7× 405 1.2× 508 2.2× 119 0.6× 92 2.9k
Zhiqi Sun China 14 1.1k 0.6× 1.0k 0.6× 154 0.5× 293 1.3× 217 1.1× 29 2.5k
Emmanuelle Planus France 26 1.2k 0.6× 628 0.4× 203 0.6× 476 2.1× 127 0.6× 51 2.1k
Yasuhiro Sawada Japan 26 1.3k 0.7× 1.3k 0.7× 441 1.3× 405 1.8× 262 1.3× 76 3.0k
Stephan Huveneers Netherlands 33 1.7k 0.9× 2.0k 1.1× 470 1.4× 390 1.7× 646 3.2× 68 4.1k
Christophe Guilluy United States 31 1.8k 1.0× 2.0k 1.1× 326 1.0× 364 1.6× 203 1.0× 43 3.7k

Countries citing papers authored by Ian Lian

Since Specialization
Citations

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

Fields of papers citing papers by Ian Lian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ian Lian

This figure shows the co-authorship network connecting the top 25 collaborators of Ian Lian. A scholar is included among the top collaborators of Ian Lian 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 Ian Lian. Ian Lian 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
1.
Yao, Chun-Wei, et al.. (2025). Corrosion Resistance and Nano-Mechanical Properties of a Superhydrophobic Surface. Lubricants. 13(1). 16–16. 2 indexed citations
2.
3.
Yao, Chun-Wei, et al.. (2025). The Elevated-Temperature Nano-Mechanical Properties of a PDMS–Silica-Based Superhydrophobic Nanocomposite Coating. Nanomaterials. 15(12). 898–898. 2 indexed citations
4.
Akhtar, Mubeena, et al.. (2024). Highly selective and sensitive N-amidothiourea-based fluorescence chemosensor for detecting Zn2+ ions and cell Imaging: Potential applications for plasma membrane detection. Journal of Photochemistry and Photobiology A Chemistry. 460. 116148–116148. 2 indexed citations
5.
Chen, Xinyu, Rui Tang, Han Guo, et al.. (2023). Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry. Scientific Reports. 13(1). 20533–20533. 3 indexed citations
6.
Hoque, Md. Ashraful, et al.. (2022). Tribocorrosion Behavior of Micro/Nanoscale Surface Coatings. Sensors. 22(24). 9974–9974. 17 indexed citations
7.
Yao, Chun-Wei, et al.. (2021). Corrosion Behavior and Mechanical Properties of a Nanocomposite Superhydrophobic Coating. Coatings. 11(6). 652–652. 15 indexed citations
8.
Li, Jingqiang, Tyler Nelson, Xin He, et al.. (2020). Dependence of Membrane Tether Strength on Substrate Rigidity Probed by Single-Cell Force Spectroscopy. The Journal of Physical Chemistry Letters. 11(10). 4173–4178. 3 indexed citations
9.
Yao, Chun-Wei, et al.. (2020). Multiscale corrosion analysis of superhydrophobic coating on 2024 aluminum alloy in a 3.5 wt% NaCl solution. MRS Communications. 10(2). 305–311. 14 indexed citations
10.
Yadav, Sakshi, et al.. (2019). A Novel Technique Enables Quantifying the Molecular Interaction of Solvents with Biological Tissues. Scientific Reports. 9(1). 9319–9319. 22 indexed citations
11.
Yao, Chun-Wei, et al.. (2018). Mechanical Durability of Engineered Superhydrophobic Surfaces for Anti-Corrosion. Coatings. 8(5). 162–162. 62 indexed citations
12.
Yao, Chun-Wei, et al.. (2018). Corrosion Resistance and Durability of Superhydrophobic Copper Surface in Corrosive NaCl Aqueous Solution. Coatings. 8(2). 70–70. 44 indexed citations
13.
Yao, Chun-Wei, et al.. (2018). Abrasion Resistance of Superhydrophobic Coatings on Aluminum Using PDMS/SiO2. Coatings. 8(11). 414–414. 36 indexed citations
14.
Taniguchi, Koji, Li‐Wha Wu, Sergei I. Grivennikov, et al.. (2015). A gp130–Src–YAP module links inflammation to epithelial regeneration. Nature. 519(7541). 57–62. 502 indexed citations breakdown →
15.
Qiao, Wen, et al.. (2014). Oil-Encapsulated Nanodroplet Array for Bio-molecular Detection. Annals of Biomedical Engineering. 42(9). 1932–1941. 14 indexed citations
16.
Yu, Fa‐Xing, Bin Zhao, Nattapon Panupinthu, et al.. (2012). Regulation of the Hippo-YAP Pathway by G-Protein-Coupled Receptor Signaling. Cell. 150(4). 780–791. 1282 indexed citations breakdown →
17.
Lian, Ian, Joungmok Kim, Hideki Okazawa, et al.. (2010). The role of YAP transcription coactivator in regulating stem cell self-renewal and differentiation. Genes & Development. 24(11). 1106–1118. 605 indexed citations breakdown →
18.
Yao, Weijuan, Jason L. Nathanson, Ian Lian, Fred H. Gage, & L A Sung. (2007). Mouse erythrocyte tropomodulin in the brain reported by lacZ knocked-in downstream from the E1 promoter. Gene Expression Patterns. 8(1). 36–46. 7 indexed citations
19.
Wu, Chia‐Ching, Yi‐Shuan Li, Jason Haga, et al.. (2006). Roles of MAP kinases in the regulation of bone matrix gene expressions in human osteoblasts by oscillatory fluid flow. Journal of Cellular Biochemistry. 98(3). 632–641. 46 indexed citations
20.
Heydarkhan‐Hagvall, Sepideh, Shu Chien, Sven Nelander, et al.. (2005). DNA microarray study on gene expression profiles in co-cultured endothelial and smooth muscle cells in response to 4- and 24-h shear stress. Molecular and Cellular Biochemistry. 281(1-2). 1–15. 29 indexed citations

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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