Grace Tan

1.8k citations
34 papers · 1.5k · h-index 17

Impact in

Papers in

    • RNA Interference and Gene Delivery 5
    • Lipid Membrane Structure and Behavior 5
    • RNA Research and Splicing 3
    • Surfactants and Colloidal Systems 7

Grace Tan

31 papers receiving 1.5k citations

Peers

Grace Tan
Comparison fields: 5 of 105
  • Pharmaceutical Science 236
  • Molecular Medicine 168
  • Biomaterials 362
  • Cancer Research 352
  • Molecular Biology 772
Replace Guillaume Bastiat with:
Guillaume Bastiat France
Aniruddha Roy India
Fateme Haghiralsadat Iran
Hima Bindu Ruttala South Korea
Mayur M. Patel India
Hongliang Du China
Bhushan S. Pattni United States
Yikun Gao China
Shumaila Shafique Pakistan
Chunrong Yang China
Grace Tan relative to Guillaume Bastiat France Guillaume Bastiat's profile →
Citations per field
00.5×5.8×
Guillaume Bastiat · 1×
Citations per year

Countries citing papers authored by Grace Tan

Since Specialization
Citations

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

Fields of papers citing papers by Grace Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Grace Tan, 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 Grace Tan Line = papers co-authored together Grace Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007321
2 2011252
3 2005157
4 2008123
5 2009102
6 200979
7 201173
8 200750
9 200542
10 200930
11 200626
12 200924
13 200818
14 200618
15 201017
16 200417
17 200917
18 201116
19 201415
20 201014

About Grace Tan

Grace Tan is a scholar working on Molecular Biology, Organic Chemistry, Biomaterials, Materials Chemistry and Electrical and Electronic Engineering, having authored 34 papers that have together received 1.5k indexed citations. Recurring topics across this work include Mesoporous Materials and Catalysis (7 papers), Surfactants and Colloidal Systems (7 papers), Supramolecular Self-Assembly in Materials (5 papers), Integrated Circuits and Semiconductor Failure Analysis (5 papers), RNA Interference and Gene Delivery (5 papers), Lipid Membrane Structure and Behavior (5 papers), MicroRNA in disease regulation (4 papers) and RNA Research and Splicing (3 papers). The work is most often cited by research in Pharmaceutical Science (236 citations), Molecular Medicine (168 citations), Biomaterials (362 citations), Cancer Research (352 citations) and Molecular Biology (772 citations). Grace Tan has collaborated with scholars based in United States, Singapore and Austria. Frequent co-authors include Vijay T. John, Marianthi Kiriakidou, Jibao He, Zissimos P. Mourelatos, Peter T. Nelson, Mariangels De Planell-Saguer, Richard G. Weiss, M. V. George, Gary L. McPherson and Barry G. Garchow. Their work appears in journals such as Langmuir, Journal of Pharmaceutical Sciences, Journal of Colloid and Interface Science, Chemical Communications and JNCI Journal of the National Cancer Institute.

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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