David Swigon

2.4k citations
59 papers · 1.8k · h-index 22

Impact in

Papers in

    • DNA and Nucleic Acid Chemistry 13
    • RNA and protein synthesis mechanisms 11
    • Protein Structure and Dynamics 5
    • Influenza Virus Research Studies 7
    • Sepsis Diagnosis and Treatment 6

David Swigon

55 papers receiving 1.7k citations

Peers

David Swigon
Comparison fields: 5 of 138
  • Modeling and Simulation 144
  • Molecular Biology 954
  • Genetics 302
  • Ecology 229
  • Cell Biology 139
Replace Claude Loverdo with:
Claude Loverdo France
Oleg A. Igoshin United States
Peter Hagedorn Denmark
Petr Chlanda Germany
Chung‐ke Chang Taiwan
Charles W. Wolgemuth United States
Christian Conrad Germany
Megan L. Stanifer Germany
Ronald W.A.L. Limpens Netherlands
Ariel Amir United States
David Swigon relative to Claude Loverdo France Claude Loverdo's profile →
Citations per field
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Citations per year

Countries citing papers authored by David Swigon

Since Specialization
Citations

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

Fields of papers citing papers by David Swigon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Swigon, 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 David Swigon Line = papers co-authored together David Swigon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004259
2 2006141
3
2000104
4 2006101
5 201194
6 200386
7 200386
8 200080
9 200077
10 200670
11 199866
12 199548
13 200441
14 201539
15 200434
16 201432
17 200832
18 201431
19 200829
20 201428

About David Swigon

David Swigon is a scholar working on Molecular Biology, Epidemiology, Genetics, Ecology and Immunology, having authored 59 papers that have together received 1.8k indexed citations. Recurring topics across this work include DNA and Nucleic Acid Chemistry (13 papers), RNA and protein synthesis mechanisms (11 papers), Bacteriophages and microbial interactions (8 papers), Bacterial Genetics and Biotechnology (7 papers), Influenza Virus Research Studies (7 papers), Sepsis Diagnosis and Treatment (6 papers), Protein Structure and Dynamics (5 papers) and Complex Systems and Time Series Analysis (5 papers). The work is most often cited by research in Modeling and Simulation (144 citations), Molecular Biology (954 citations), Genetics (302 citations), Ecology (229 citations) and Cell Biology (139 citations). David Swigon has collaborated with scholars based in United States, South Korea and Austria. Frequent co-authors include Bernard D. Coleman, Wilma K. Olson, Irwin Tobias, Gilles Clermont, Baris Hancioglu, Luke Czapla, Katsuhiko Murakami, Richard H. Ebright, Helen M. Berman and Seth A. Darst. Their work appears in journals such as Journal of Theoretical Biology, Biophysical Journal, SIAM Journal on Applied Dynamical Systems, PLoS ONE and Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences.

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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