Brian D. Quinlan

2.5k total citations · 2 hit papers
17 papers, 1.3k citations indexed

About

Brian D. Quinlan is a scholar working on Infectious Diseases, Virology and Immunology. According to data from OpenAlex, Brian D. Quinlan has authored 17 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Infectious Diseases, 9 papers in Virology and 7 papers in Immunology. Recurrent topics in Brian D. Quinlan's work include HIV Research and Treatment (9 papers), SARS-CoV-2 and COVID-19 Research (6 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Brian D. Quinlan is often cited by papers focused on HIV Research and Treatment (9 papers), SARS-CoV-2 and COVID-19 Research (6 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Brian D. Quinlan collaborates with scholars based in United States, China and Netherlands. Brian D. Quinlan's co-authors include Michael Farzan, Hyeryun Choe, Lizhou Zhang, Amrita Ojha, Cody B. Jackson, Huihui Mou, Wenhui Li, Haiyong Peng, Christoph Rader and Erumbi S. Rangarajan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Brian D. Quinlan

17 papers receiving 1.2k citations

Hit Papers

SARS-CoV-2 spike-protein D614G mutation increases virion ... 2020 2026 2022 2024 2020 2023 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian D. Quinlan United States 12 819 430 290 160 148 17 1.3k
Yi-Min Zheng United States 21 1.0k 1.2× 468 1.1× 486 1.7× 192 1.2× 164 1.1× 35 1.6k
Harry B. Gristick United States 13 951 1.2× 612 1.4× 291 1.0× 130 0.8× 341 2.3× 22 1.4k
Louis-Marie Bloyet United States 15 744 0.9× 318 0.7× 140 0.5× 163 1.0× 78 0.5× 23 1.1k
Yu E. Lee United States 6 1.0k 1.2× 407 0.9× 206 0.7× 180 1.1× 69 0.5× 9 1.2k
Kim-Marie A. Dam United States 7 844 1.0× 342 0.8× 155 0.5× 121 0.8× 98 0.7× 11 1.0k
David Franco United States 21 424 0.5× 352 0.8× 205 0.7× 65 0.4× 256 1.7× 34 1.0k
Kshitij Wagh United States 16 568 0.7× 294 0.7× 281 1.0× 68 0.4× 489 3.3× 28 1.1k
Benjamin Petsch Germany 18 1.0k 1.2× 1.1k 2.6× 547 1.9× 220 1.4× 121 0.8× 33 2.0k
Meredith E. Davis-Gardner United States 17 521 0.6× 504 1.2× 640 2.2× 110 0.7× 120 0.8× 27 1.3k
Florian Douam United States 21 568 0.7× 309 0.7× 274 0.9× 59 0.4× 76 0.5× 37 1.2k

Countries citing papers authored by Brian D. Quinlan

Since Specialization
Citations

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

Fields of papers citing papers by Brian D. Quinlan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian D. Quinlan

This figure shows the co-authorship network connecting the top 25 collaborators of Brian D. Quinlan. A scholar is included among the top collaborators of Brian D. Quinlan 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 D. Quinlan. Brian D. Quinlan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Yin, Yiming, Yan Guo, Yuxuan Jiang, et al.. (2024). In vivo affinity maturation of mouse B cells reprogrammed to express human antibodies. Nature Biomedical Engineering. 8(4). 361–379. 9 indexed citations
2.
Zhang, Lizhou, Kunal R. More, Amrita Ojha, et al.. (2023). Effect of mRNA-LNP components of two globally-marketed COVID-19 vaccines on efficacy and stability. npj Vaccines. 8(1). 156–156. 105 indexed citations breakdown →
3.
He, Wenhui, Tianling Ou, Nickolas K. Skamangas, et al.. (2023). Heavy-chain CDR3-engineered B cells facilitate in vivo evaluation of HIV-1 vaccine candidates. Immunity. 56(10). 2408–2424.e6. 9 indexed citations
4.
Ou, Tianling, Wenhui He, Brian D. Quinlan, et al.. (2021). Reprogramming of the heavy-chain CDR3 regions of a human antibody repertoire. Molecular Therapy. 30(1). 184–197. 10 indexed citations
5.
Mou, Huihui, Brian D. Quinlan, Haiyong Peng, et al.. (2021). Mutations derived from horseshoe bat ACE2 orthologs enhance ACE2-Fc neutralization of SARS-CoV-2. PLoS Pathogens. 17(4). e1009501–e1009501. 34 indexed citations
6.
Guo, Yan, Wenhui He, Huihui Mou, et al.. (2021). An Engineered Receptor-Binding Domain Improves the Immunogenicity of Multivalent SARS-CoV-2 Vaccines. mBio. 12(3). 19 indexed citations
7.
Xiao, Tianshu, Jianming Lü, Jun Zhang, et al.. (2021). A trimeric human angiotensin-converting enzyme 2 as an anti-SARS-CoV-2 agent. Nature Structural & Molecular Biology. 28(2). 202–209. 88 indexed citations
8.
Yin, Yiming, Brian D. Quinlan, Tianling Ou, et al.. (2021). In vitro affinity maturation of broader and more-potent variants of the HIV-1–neutralizing antibody CAP256-VRC26.25. Proceedings of the National Academy of Sciences. 118(29). 6 indexed citations
9.
Zhang, Lizhou, Cody B. Jackson, Huihui Mou, et al.. (2020). SARS-CoV-2 spike-protein D614G mutation increases virion spike density and infectivity. Nature Communications. 11(1). 6013–6013. 662 indexed citations breakdown →
10.
Quinlan, Brian D., Huihui Mou, Lizhou Zhang, et al.. (2020). The SARS-CoV-2 Receptor-Binding Domain Elicits a Potent Neutralizing Response Without Antibody-Dependent Enhancement. SSRN Electronic Journal. 26 indexed citations
11.
Otsuka, Yuka, Kimberly Schmitt, Brian D. Quinlan, et al.. (2018). Diverse pathways of escape from all well-characterized VRC01-class broadly neutralizing HIV-1 antibodies. PLoS Pathogens. 14(8). e1007238–e1007238. 11 indexed citations
12.
Gardner, Matthew R., et al.. (2016). CD4-Induced Antibodies Promote Association of the HIV-1 Envelope Glycoprotein with CD4-Binding Site Antibodies. Journal of Virology. 90(17). 7822–7832. 15 indexed citations
13.
Quinlan, Brian D., et al.. (2014). A Double-Mimetic Peptide Efficiently Neutralizes HIV-1 by Bridging the CD4- and Coreceptor-Binding Sites of gp120. Journal of Virology. 88(6). 3353–3358. 16 indexed citations
14.
Quinlan, Brian D., et al.. (2013). Direct Expression and Validation of Phage-selected Peptide Variants in Mammalian Cells. Journal of Biological Chemistry. 288(26). 18803–18810. 8 indexed citations
15.
Chiang, Jessica J., Matthew R. Gardner, Brian D. Quinlan, et al.. (2012). Enhanced Recognition and Neutralization of HIV-1 by Antibody-Derived CCR5-Mimetic Peptide Variants. Journal of Virology. 86(22). 12417–12421. 20 indexed citations
16.
Dorfman, Tatyana, Brian D. Quinlan, Jessica J. Chiang, et al.. (2011). A Tyrosine-Sulfated CCR5-Mimetic Peptide Promotes Conformational Transitions in the HIV-1 Envelope Glycoprotein. Journal of Virology. 85(15). 7563–7571. 17 indexed citations
17.
Uchil, Pradeep D., Brian D. Quinlan, Wai-Tsing Chan, Joseph M. Luna, & Walther Mothes. (2008). TRIM E3 Ligases Interfere with Early and Late Stages of the Retroviral Life Cycle. PLoS Pathogens. 4(2). e16–e16. 198 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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