Fai Siu

2.7k citations
16 papers · 2.2k · 1 hit paper · h-index 15

Impact in

Papers in

    • Receptor Mechanisms and Signaling 6
    • RNA and protein synthesis mechanisms 3
    • RNA Research and Splicing 2
    • Endoplasmic Reticulum Stress and Disease 4

Fai Siu

16 papers receiving 2.2k citations

Hit Papers

Structural Features for Functional Selectivity at Serotonin Receptors 2013 · 543 citations
5430+4+8Years since publication100200300400500

Peers

Fai Siu
Comparison fields: 5 of 102
  • Cellular and Molecular Neuroscience 740
  • Molecular Biology 1.9k
  • Cell Biology 286
  • Structural Biology 22
  • Endocrinology, Diabetes and Metabolism 179
Replace Francesca Magnani with:
Francesca Magnani Italy
Katie Leach Australia
A.S. Dore United Kingdom
Hanne B. Rasmussen Denmark
David M. Thal Australia
Hongli Hu China
Dean P. Staus United States
Pengxiang Huang United States
Chenbo Zeng United States
Weijiao Huang United States
Fai Siu relative to Francesca Magnani Italy Francesca Magnani's profile →
Citations per field
00.5×3.0×
Francesca Magnani · 1×
Citations per year

Countries citing papers authored by Fai Siu

Since Specialization
Citations

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

Fields of papers citing papers by Fai Siu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Fai Siu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fai Siu Line = papers co-authored together Fai Siu links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Structural Features for Functional Selectivity at Serotonin Receptors
Hit paper breakdown →
2013543
2 2013369
3 2013298
4 2002223
5 2013144
6 2013110
7 2000101
8 200393
9 201592
10 200167
11 200651
12 196640
13 200539
14 196725
15 201414
16 20201

About Fai Siu

Fai Siu is a scholar working on Molecular Biology, Cell Biology, Genetics, Cellular and Molecular Neuroscience and Organic Chemistry, having authored 16 papers that have together received 2.2k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (6 papers), Endoplasmic Reticulum Stress and Disease (4 papers), RNA and protein synthesis mechanisms (3 papers), Pancreatic function and diabetes (2 papers), Bacterial Genetics and Biotechnology (2 papers), Neuropeptides and Animal Physiology (2 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers) and RNA Research and Splicing (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (740 citations), Molecular Biology (1.9k citations), Cell Biology (286 citations), Structural Biology (22 citations) and Endocrinology, Diabetes and Metabolism (179 citations). Fai Siu has collaborated with scholars based in United States, Netherlands and China. Frequent co-authors include Raymond C. Stevens, Vsevolod Katritch, Michael S. Kilberg, Gye Won Han, Vadim Cherezov, Chong Wang, Xi‐Ping Huang, Bryan L. Roth, Daniel Wacker and Wei Liu. Their work appears in journals such as Journal of Biological Chemistry, Nature, Nature Methods, Science and Nature Structural & Molecular Biology.

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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