Quinlin Hanson

440 total citations
8 papers, 210 citations indexed

About

Quinlin Hanson is a scholar working on Molecular Biology, Infectious Diseases and Computational Theory and Mathematics. According to data from OpenAlex, Quinlin Hanson has authored 8 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Infectious Diseases and 3 papers in Computational Theory and Mathematics. Recurrent topics in Quinlin Hanson's work include Computational Drug Discovery Methods (3 papers), Glycosylation and Glycoproteins Research (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Quinlin Hanson is often cited by papers focused on Computational Drug Discovery Methods (3 papers), Glycosylation and Glycoproteins Research (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Quinlin Hanson collaborates with scholars based in United States. Quinlin Hanson's co-authors include Adam W. Barb, Ganesh P. Subedi, Min Shen, Matthew D. Hall, Richard T. Eastman, Kelli M. Wilson, Zina Itkin, Paul Shinn, Eric S. Underbakke and Brian C. Smith and has published in prestigious journals such as Journal of Molecular Biology, Biochemistry and Structure.

In The Last Decade

Quinlin Hanson

8 papers receiving 209 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Quinlin Hanson United States	5	132	99	63	47	41	8	210
Francis Gaudreault Canada	10	214 1.6×	62 0.6×	27 0.4×	15 0.3×	51 1.2×	18	275
Sebastian Pomplun Germany	13	324 2.5×	64 0.6×	72 1.1×	20 0.4×	25 0.6×	23	402
Hristo L. Svilenov Germany	14	327 2.5×	203 2.1×	27 0.4×	56 1.2×	23 0.6×	31	401
Nicholas J. Rettko United States	6	185 1.4×	61 0.6×	150 2.4×	32 0.7×	19 0.5×	8	321
Puneet Rawat India	13	331 2.5×	152 1.5×	65 1.0×	46 1.0×	65 1.6×	27	424
Sakshi Gautam United States	11	264 2.0×	34 0.3×	38 0.6×	23 0.5×	36 0.9×	27	365
Ana Diniz Portugal	10	225 1.7×	30 0.3×	44 0.7×	115 2.4×	8 0.2×	13	303
Steve Agajanian United States	11	266 2.0×	56 0.6×	133 2.1×	12 0.3×	132 3.2×	17	374
James E. Lucas United States	6	304 2.3×	35 0.4×	22 0.3×	15 0.3×	36 0.9×	8	349
Karin E. J. Rödström Sweden	9	178 1.3×	33 0.3×	53 0.8×	95 2.0×	7 0.2×	13	313

Countries citing papers authored by Quinlin Hanson

Since Specialization

Citations

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

Fields of papers citing papers by Quinlin Hanson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Quinlin Hanson

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Hanson, Quinlin, Xin Hu, Lin Ye, et al.. (2025). A High-Throughput Screening Pipeline to Identify Methyltransferase and Exonuclease Inhibitors of SARS-CoV-2 NSP14. Biochemistry. 64(2). 419–431. 1 indexed citations

2.

Hanson, Quinlin, et al.. (2025). Discovery of SARS-CoV-2 Nsp14-Methyltransferase (MTase) Inhibitors by Harnessing Scaffold-Centric Exploration of the Ultra Large Chemical Space. ACS Pharmacology & Translational Science. 8(5). 1366–1400. 1 indexed citations

3.

Hanson, Quinlin, Min Shen, Hui Guo, et al.. (2023). Target Class Profiling of Small-Molecule Methyltransferases. ACS Chemical Biology. 18(4). 969–981. 2 indexed citations

4.

Jain, Sankalp, Bolormaa Baljinnyam, Quinlin Hanson, et al.. (2021). Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants. ACS Pharmacology & Translational Science. 4(5). 1675–1688. 10 indexed citations

5.

Hanson, Quinlin, Kelli M. Wilson, Min Shen, et al.. (2020). Targeting ACE2–RBD Interaction as a Platform for COVID-19 Therapeutics: Development and Drug-Repurposing Screen of an AlphaLISA Proximity Assay. ACS Pharmacology & Translational Science. 3(6). 1352–1360. 63 indexed citations

6.

Hanson, Quinlin, et al.. (2018). Calmodulin-induced Conformational Control and Allostery Underlying Neuronal Nitric Oxide Synthase Activation. Journal of Molecular Biology. 430(7). 935–947. 19 indexed citations

7.

Hanson, Quinlin & Adam W. Barb. (2015). A Perspective on the Structure and Receptor Binding Properties of Immunoglobulin G Fc. Biochemistry. 54(19). 2931–2942. 45 indexed citations

8.

Subedi, Ganesh P., Quinlin Hanson, & Adam W. Barb. (2014). Restricted Motion of the Conserved Immunoglobulin G1 N-Glycan Is Essential for Efficient FcγRIIIa Binding. Structure. 22(10). 1478–1488. 69 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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