Taylor R. Quinn

730 citations
12 papers · 415 indexed · h-index 7
Topics
Protein Structure and Dynamics (3 papers)Machine Learning in Materials Science (3 papers)Computational Drug Discovery Methods (3 papers)

In The Last Decade

Taylor R. Quinn

11 papers receiving 415 citations

Peers

Taylor R. Quinn
Comparison fields: 5 of 50
  • Organic Chemistry 251
  • Molecular Biology 131
  • Materials Chemistry 58
  • Inorganic Chemistry 44
  • Renewable Energy, Sustainability and the Environment 33
Replace Margarita Escudero‐Casao with:
Margarita Escudero‐Casao Italy
Yatao Qiu China
Joseph Katigbak United States
Lourdusamy Emmanuvel India
Manian Rajesh Kumar South Korea
Sherif J. Kaldas Canada
Nicole End Switzerland
Churl Min Seong South Korea
Jean-François Brazeau United States
Alexander R. Nödling United Kingdom
Taylor R. Quinn relative to Margarita Escudero‐Casao Italy Margarita Escudero‐Casao's profile →
Citations per field
00.5×2.8×
Margarita Escudero‐Casao · 1×
Citations per year

Countries citing papers authored by Taylor R. Quinn

Since Specialization
Citations

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

Fields of papers citing papers by Taylor R. Quinn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Taylor R. Quinn. 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 Taylor R. Quinn. The network helps show where Taylor R. Quinn may publish in the future.

Co-authorship network of co-authors of Taylor R. Quinn

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 6
2 9
3 7
4 1
5 98
6 10
7 45
8 230
9 1
10 7
11 0
12 1

About Taylor R. Quinn

Taylor R. Quinn is a scholar working on Physiology, Computational Theory and Mathematics and Molecular Biology, having authored 12 papers that have together received 415 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Machine Learning in Materials Science (3 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Organic Chemistry (251 citations), Pharmaceutical Science (24 citations) and Inorganic Chemistry (44 citations). Taylor R. Quinn has collaborated with scholars based in United States, China and Philippines. Frequent co-authors include Olaf Wiest, Klaus Harms, Xiaoqiang Huang, Eric Meggers, Richard D. Webster, Lilu Zhang, Paul Helquist, Jack F. Shern, Marielle E. Yohe and Rossella Rota. Their work appears in journals such as Journal of the American Chemical Society, Nature Communications and PLoS ONE.

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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