Nathan Collins

985 citations
30 papers · 755 · h-index 14

Impact in

Papers in

Nathan Collins

29 papers receiving 714 citations

Peers

Nathan Collins
Comparison fields: 5 of 96
  • Cellular and Molecular Neuroscience 281
  • Molecular Biology 508
  • Spectroscopy 91
  • Computational Theory and Mathematics 47
  • Organic Chemistry 79
Replace George J. Turner with:
George J. Turner United States
Gianluigi Caltabiano Spain
Artur Giełdoń Poland
S. Runge Germany
Min‐Kyu Cho Germany
Michael E. Cooper United Kingdom
Siew Peng Ho United States
Piotr F. J. Lipiński Poland
Ching‐Ju Tsai Switzerland
Shixin Ye France
Nathan Collins relative to George J. Turner United States George J. Turner's profile →
Citations per field
00.5×1.5×
George J. Turner · 1×
Citations per year

Countries citing papers authored by Nathan Collins

Since Specialization
Citations

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

Fields of papers citing papers by Nathan Collins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nathan Collins, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nathan Collins Line = papers co-authored together Nathan Collins links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995196
2 200088
3 199677
4 202056
5 199452
6 200345
7 199630
8 200427
9 201025
10 199318
11 199618
12 200417
13 199416
14 199716
15 199411
16 19958
17 20108
18 19828
19 20188
20 19957

About Nathan Collins

Nathan Collins is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Biomedical Engineering, Computational Theory and Mathematics and Spectroscopy, having authored 30 papers that have together received 755 indexed citations. Recurring topics across this work include Chemical Synthesis and Analysis (12 papers), Neuropeptides and Animal Physiology (8 papers), Receptor Mechanisms and Signaling (6 papers), Innovative Microfluidic and Catalytic Techniques Innovation (5 papers), Computational Drug Discovery Methods (3 papers), Pharmacological Receptor Mechanisms and Effects (3 papers), Lipid Membrane Structure and Behavior (2 papers) and Analytical Chemistry and Chromatography (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (281 citations), Molecular Biology (508 citations), Spectroscopy (91 citations), Computational Theory and Mathematics (47 citations) and Organic Chemistry (79 citations). Nathan Collins has collaborated with scholars based in United States, Poland and New Zealand. Frequent co-authors include Victor J. Hruby, Henry I. Yamamura, William R. Roeske, Ewa Malatyńska, Jean Y. Wang, Richard J. Knapp, Lei Fang, Edward K. Han, Sajid Khan Tahir and Sajeev Cherian. Their work appears in journals such as Journal of the American Chemical Society, Regulatory Peptides, Journal of Medicinal Chemistry, British Journal of Cancer and Journal of Flow Chemistry.

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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