Brian M. Paegel

3.3k total citations
51 papers, 2.5k citations indexed

About

Brian M. Paegel is a scholar working on Molecular Biology, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Brian M. Paegel has authored 51 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 32 papers in Biomedical Engineering and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Brian M. Paegel's work include Innovative Microfluidic and Catalytic Techniques Innovation (25 papers), Chemical Synthesis and Analysis (21 papers) and Microfluidic and Capillary Electrophoresis Applications (20 papers). Brian M. Paegel is often cited by papers focused on Innovative Microfluidic and Catalytic Techniques Innovation (25 papers), Chemical Synthesis and Analysis (21 papers) and Microfluidic and Capillary Electrophoresis Applications (20 papers). Brian M. Paegel collaborates with scholars based in United States, Switzerland and Japan. Brian M. Paegel's co-authors include Richard A. Mathies, Alexander K. Price, James R. Scherer, Robert G. Blazej, Sandro Matosevic, V. Cavett, Charles A. Emrich, Gerald F. Joyce, Gary J. Wedemayer and Peter C. Simpson and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Brian M. Paegel

50 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian M. Paegel United States 27 1.4k 1.3k 457 425 290 51 2.5k
Amy T. Lu United States 8 555 0.4× 1.6k 1.3× 292 0.6× 231 0.5× 368 1.3× 9 2.3k
Anthony G. Frutos United States 19 1.0k 0.7× 1.9k 1.5× 75 0.2× 664 1.6× 322 1.1× 32 2.6k
Martin Bartošík Czechia 20 484 0.4× 1.4k 1.1× 113 0.2× 411 1.0× 64 0.2× 54 1.8k
Thomas Tørring Denmark 15 487 0.4× 1.4k 1.1× 208 0.5× 128 0.3× 122 0.4× 34 1.7k
Martin Fischlechner United Kingdom 19 1.9k 1.4× 793 0.6× 104 0.2× 935 2.2× 62 0.2× 29 2.6k
Heather D. Agnew United States 14 160 0.1× 690 0.5× 279 0.6× 156 0.4× 239 0.8× 18 1.0k
Jeffrey D. Carbeck United States 24 726 0.5× 731 0.6× 122 0.3× 218 0.5× 65 0.2× 36 1.6k
Steffen Nock Germany 19 521 0.4× 1.2k 1.0× 51 0.1× 273 0.6× 491 1.7× 33 1.7k
Hequan Yao United States 11 646 0.5× 908 0.7× 217 0.5× 112 0.3× 138 0.5× 13 1.6k
Colin D. Medley United States 20 1.2k 0.9× 2.4k 1.8× 60 0.1× 225 0.5× 196 0.7× 32 2.9k

Countries citing papers authored by Brian M. Paegel

Since Specialization
Citations

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

Fields of papers citing papers by Brian M. Paegel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian M. Paegel. 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 Brian M. Paegel. The network helps show where Brian M. Paegel may publish in the future.

Co-authorship network of co-authors of Brian M. Paegel

This figure shows the co-authorship network connecting the top 25 collaborators of Brian M. Paegel. A scholar is included among the top collaborators of Brian M. Paegel 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 Brian M. Paegel. Brian M. Paegel 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.
Cavett, V., Fred R. Ward, Kim F. McClure, et al.. (2024). Activity-Based DNA-Encoded Library Screening for Selective Inhibitors of Eukaryotic Translation. ACS Central Science. 10(10). 1960–1968. 3 indexed citations
2.
Chan, Alix I, et al.. (2023). Liposomal Permeation Assay for Droplet-Scale Pharmacokinetic Screening. Journal of Medicinal Chemistry. 66(9). 6288–6296. 4 indexed citations
3.
Cavett, V., Alix I Chan, Christian N. Cunningham, & Brian M. Paegel. (2023). Hydrogel-Encapsulated Beads Enable Proximity-Driven Encoded Library Synthesis and Screening. ACS Central Science. 9(8). 1603–1610. 2 indexed citations
4.
Paegel, Brian M., et al.. (2023). Highly Parallelized Screening of Functionally Enhanced XNA Aptamers in Uniform Hydrogel Particles. ACS Synthetic Biology. 12(7). 2127–2134. 10 indexed citations
5.
Paegel, Brian M., et al.. (2023). Dose–Response Activity-Based DNA-Encoded Library Screening. ACS Medicinal Chemistry Letters. 14(9). 1295–1303. 5 indexed citations
6.
Gibaut, Quentin M. R., et al.. (2022). Study of an RNA-Focused DNA-Encoded Library Informs Design of a Degrader of a r(CUG) Repeat Expansion. Journal of the American Chemical Society. 144(48). 21972–21979. 22 indexed citations
7.
Benhamou, Raphael I., Blessy M. Suresh, Yuquan Tong, et al.. (2022). DNA-encoded library versus RNA-encoded library selection enables design of an oncogenic noncoding RNA inhibitor. Proceedings of the National Academy of Sciences. 119(6). 41 indexed citations
8.
Blackmond, Donna G., et al.. (2021). Chiral lipid bilayers are enantioselectively permeable. Nature Chemistry. 13(8). 786–791. 45 indexed citations
9.
Paegel, Brian M., et al.. (2020). DNA-Encoded Chemistry: Drug Discovery from a Few Good Reactions. Chemical Reviews. 121(12). 7155–7177. 157 indexed citations
10.
Quốc, Vương Đặng, et al.. (2019). Off-DNA DNA-Encoded Library Affinity Screening. ACS Combinatorial Science. 22(1). 25–34. 27 indexed citations
11.
Nikoomanzar, Ali, et al.. (2019). Fluorescence-Activated Droplet Sorting for Single-Cell Directed Evolution. ACS Synthetic Biology. 8(6). 1430–1440. 96 indexed citations
12.
Ndungu, John M., V. Cavett, Patrick J. McEnaney, et al.. (2016). High-throughput Identification of DNA-Encoded IgG Ligands that Distinguish Active and LatentMycobacterium tuberculosisInfections. ACS Chemical Biology. 12(1). 234–243. 55 indexed citations
13.
Matosevic, Sandro & Brian M. Paegel. (2013). Layer-by-layer cell membrane assembly. Nature Chemistry. 5(11). 958–963. 131 indexed citations
14.
Matosevic, Sandro & Brian M. Paegel. (2012). Layer-By-Layer Assembly of Cellular Structures. Biophysical Journal. 102(3). 28a–28a. 1 indexed citations
15.
Paegel, Brian M. & Gerald F. Joyce. (2010). Microfluidic Compartmentalized Directed Evolution. Chemistry & Biology. 17(7). 717–724. 56 indexed citations
16.
Paegel, Brian M. & Gerald F. Joyce. (2008). Darwinian Evolution on a Chip. PLoS Biology. 6(4). e85–e85. 22 indexed citations
17.
Paegel, Brian M., William H. Grover, Alison M. Skelley, Richard A. Mathies, & Gerald F. Joyce. (2006). Microfluidic Serial Dilution Circuit. Analytical Chemistry. 78(21). 7522–7527. 51 indexed citations
18.
Doherty, Erin A. S., et al.. (2004). Sparsely Cross-Linked “Nanogel” Matrixes as Fluid, Mechanically Stabilized Polymer Networks for High-Throughput Microchannel DNA Sequencing. Analytical Chemistry. 76(18). 5249–5256. 26 indexed citations
19.
Paegel, Brian M., Charles A. Emrich, Gary J. Wedemayer, James R. Scherer, & Richard A. Mathies. (2002). High throughput DNA sequencing with a microfabricated 96-lane capillary array electrophoresis bioprocessor. Proceedings of the National Academy of Sciences. 99(2). 574–579. 195 indexed citations
20.
Medintz, Igor L., Brian M. Paegel, Robert G. Blazej, et al.. (2001). High-performance genetic analysis using microfabricated capillary array electrophoresis microplates. Electrophoresis. 22(18). 3845–3856. 64 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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