Gabriel A. Kwong

4.3k total citations
49 papers, 3.2k citations indexed

About

Gabriel A. Kwong is a scholar working on Molecular Biology, Biomedical Engineering and Oncology. According to data from OpenAlex, Gabriel A. Kwong has authored 49 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 16 papers in Biomedical Engineering and 11 papers in Oncology. Recurrent topics in Gabriel A. Kwong's work include Advanced biosensing and bioanalysis techniques (15 papers), Advanced Biosensing Techniques and Applications (8 papers) and Monoclonal and Polyclonal Antibodies Research (7 papers). Gabriel A. Kwong is often cited by papers focused on Advanced biosensing and bioanalysis techniques (15 papers), Advanced Biosensing Techniques and Applications (8 papers) and Monoclonal and Polyclonal Antibodies Research (7 papers). Gabriel A. Kwong collaborates with scholars based in United States, Russia and Singapore. Gabriel A. Kwong's co-authors include James R. Heath, Sangeeta N. Bhatia, Caius G. Radu, Rong Fan, Habib Ahmad, Chao Liu, Young Shik Shin, Yuri L. Bunimovich, Woon‐Seok Yeo and Andrew Warren and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Angewandte Chemie International Edition.

In The Last Decade

Gabriel A. Kwong

47 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gabriel A. Kwong United States 24 1.8k 1.7k 411 400 309 49 3.2k
Jin‐Min Nam Japan 21 1.3k 0.7× 2.1k 1.2× 251 0.6× 371 0.9× 242 0.8× 34 3.5k
Piotr Grodzinski United States 30 3.1k 1.8× 1.3k 0.7× 860 2.1× 243 0.6× 193 0.6× 88 4.8k
Rubul Mout United States 26 1.2k 0.7× 2.5k 1.4× 234 0.6× 195 0.5× 264 0.9× 42 4.3k
Zhifeng Shao United States 34 595 0.3× 1.8k 1.1× 335 0.8× 117 0.3× 656 2.1× 91 4.0k
Theodore K. Christopoulos Greece 29 1.4k 0.8× 2.2k 1.3× 344 0.8× 104 0.3× 103 0.3× 118 3.5k
Hai‐Yan Xie China 43 2.4k 1.4× 2.4k 1.4× 503 1.2× 470 1.2× 599 1.9× 125 5.3k
Mahmoud Labib Canada 35 1.7k 1.0× 2.2k 1.3× 675 1.6× 490 1.2× 96 0.3× 66 3.5k
Youli Zu United States 37 1.2k 0.7× 3.1k 1.8× 162 0.4× 1.3k 3.1× 838 2.7× 141 5.2k
Ian M. White United States 28 2.7k 1.5× 1.8k 1.1× 2.0k 4.9× 666 1.7× 91 0.3× 73 5.4k
Tatyana Levchenko United States 30 864 0.5× 2.7k 1.5× 107 0.3× 236 0.6× 258 0.8× 53 4.0k

Countries citing papers authored by Gabriel A. Kwong

Since Specialization
Citations

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

Fields of papers citing papers by Gabriel A. Kwong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gabriel A. Kwong. 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 Gabriel A. Kwong. The network helps show where Gabriel A. Kwong may publish in the future.

Co-authorship network of co-authors of Gabriel A. Kwong

This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel A. Kwong. A scholar is included among the top collaborators of Gabriel A. Kwong 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 Gabriel A. Kwong. Gabriel A. Kwong 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.
Yellman, Christopher M., Hee Jun Lee, Hathaichanok Phuengkham, et al.. (2025). A facile yeast-display approach for antibody mask discovery. Protein Engineering Design and Selection. 38. 1 indexed citations
2.
3.
Wang, Bryan, Ye Li, Jing Li, et al.. (2025). Label-free in-line characterization of immune cell culture using quantitative phase imaging. npj Regenerative Medicine. 10(1). 56–56.
4.
Gamboa, Lena, Hee Jun Lee, Hathaichanok Phuengkham, et al.. (2025). Sensitizing solid tumors to CAR-mediated cytotoxicity by lipid nanoparticle delivery of synthetic antigens. Nature Cancer. 6(6). 1073–1087. 3 indexed citations
5.
Sivakumar, Anirudh, Hathaichanok Phuengkham, Swapnil Bawage, et al.. (2025). AND-gated protease-activated nanosensors for programmable detection of anti-tumour immunity. Nature Nanotechnology. 20(3). 441–450. 6 indexed citations
6.
Kwong, Gabriel A., et al.. (2024). In vivo gene delivery to immune cells. Current Opinion in Biotechnology. 88. 103169–103169. 3 indexed citations
7.
Hua, Xuanwen, Biagio Mandracchia, Wenhao Liu, et al.. (2024). Light-field flow cytometry for high-resolution, volumetric and multiparametric 3D single-cell analysis. Nature Communications. 15(1). 1975–1975. 22 indexed citations
8.
Wood, Levi B., et al.. (2024). Quantifying UV-induced photodamage for longitudinal live-cell imaging applications of deep-UV microscopy. Biomedical Optics Express. 16(1). 208–208. 4 indexed citations
9.
Mandracchia, Biagio, et al.. (2023). Portable light-sheet optofluidic microscopy for 3D fluorescence imaging flow cytometry. Lab on a Chip. 23(4). 624–630. 11 indexed citations
10.
Gamboa, Lena, Swapnil Bawage, Hathaichanok Phuengkham, et al.. (2022). In vivo mRNA delivery to virus-specific T cells by light-induced ligand exchange of MHC class I antigen-presenting nanoparticles. Science Advances. 8(8). eabm7950–eabm7950. 44 indexed citations
11.
Holt, Brandon Alexander, et al.. (2022). Embracing Enzyme Promiscuity With Activity-Based Compressed Biosensing. SSRN Electronic Journal. 1 indexed citations
12.
Bazrafshan, Alisina, Brandon Alexander Holt, Hanquan Su, et al.. (2021). DNA Gold Nanoparticle Motors Demonstrate Processive Motion with Bursts of Speed Up to 50 nm Per Second. ACS Nano. 15(5). 8427–8438. 37 indexed citations
13.
Sivakumar, Anirudh, et al.. (2021). Interfacing Biomaterials with Synthetic T Cell Immunity. Advanced Healthcare Materials. 10(15). e2100157–e2100157. 6 indexed citations
14.
Kwong, Gabriel A., Sharmistha Ghosh, Lena Gamboa, et al.. (2021). Synthetic biomarkers: a twenty-first century path to early cancer detection. Nature reviews. Cancer. 21(10). 655–668. 130 indexed citations
15.
16.
Holt, Brandon Alexander & Gabriel A. Kwong. (2020). Protease circuits for processing biological information. Nature Communications. 11(1). 5021–5021. 21 indexed citations
17.
Romanyuk, Andrey, et al.. (2020). STAR particles for enhanced topical drug and vaccine delivery. Nature Medicine. 26(3). 341–347. 49 indexed citations
18.
Holt, Brandon Alexander, et al.. (2019). Non-invasive early detection of acute transplant rejection via nanosensors of granzyme B activity. Nature Biomedical Engineering. 3(4). 281–291. 85 indexed citations
19.
Lin, Kevin, Gabriel A. Kwong, Andrew Warren, David K. Wood, & Sangeeta N. Bhatia. (2013). Nanoparticles That Sense Thrombin Activity As Synthetic Urinary Biomarkers of Thrombosis. ACS Nano. 7(10). 9001–9009. 91 indexed citations
20.
Maltzahn, Geoffrey von, Gayathree Murugappan, Steven Mo, et al.. (2011). Mass-encoded synthetic biomarkers for multiplexed urinary monitoring of disease. DSpace@MIT (Massachusetts Institute of Technology). 151 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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