Julia Paxson

441 citations
13 papers · 325 · h-index 10

Impact in

  • Equine top 5%
    • Veterinary Equine Medical Research
  • Genetics top 10%
    • Mesenchymal stem cell research
    • Virus-based gene therapy research

Papers in

    • Mesenchymal stem cell research 4
    • Tissue Engineering and Regenerative Medicine 2

Julia Paxson

12 papers receiving 321 citations

Peers

Julia Paxson
Comparison fields: 5 of 65
  • Equine 27
  • Genetics 75
  • Drug Discovery 1
  • Pulmonary and Respiratory Medicine 122
  • Surgery 105
Replace Masato KUWABARA with:
Masato KUWABARA Japan
Renata L. Linardi United States
Nora L. Springer United States
Anthony D. Pardo United States
Rafael Tapia‐Limonchi Peru
C. Perrini Italy
Merry Z. C. Ruan United States
Yutaka Momota Japan
Lakshman Chelvarajan United States
Yupeng Yin China
Julia Paxson relative to Masato KUWABARA Japan Masato KUWABARA's profile →
Citations per field
00.5×
Masato KUWABARA · 1×
Citations per year

Countries citing papers authored by Julia Paxson

Since Specialization
Citations

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

Fields of papers citing papers by Julia Paxson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Julia Paxson, 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 Julia Paxson Line = papers co-authored together Julia Paxson links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 201180
2 201151
3
In vitro and in vivo kinetics of recombinant vaccinia virus cancer-gene therapy.
199433
4 201533
5 201328
6 201526
7 200925
8 201519
9 201615
10 200712
11 20082
12 20101
13 20190

About Julia Paxson

Julia Paxson is a scholar working on Genetics, Surgery, Pulmonary and Respiratory Medicine, Equine and Rehabilitation, having authored 13 papers that have together received 325 indexed citations. Recurring topics across this work include Mesenchymal stem cell research (4 papers), Veterinary Equine Medical Research (3 papers), Cellular Mechanics and Interactions (2 papers), Tissue Engineering and Regenerative Medicine (2 papers), Neonatal Respiratory Health Research (2 papers), Carcinogens and Genotoxicity Assessment (1 paper), Toxic Organic Pollutants Impact (1 paper) and 3D Printing in Biomedical Research (1 paper). The work is most often cited by research in Equine (27 citations), Genetics (75 citations), Drug Discovery (1 citation), Pulmonary and Respiratory Medicine (122 citations) and Surgery (105 citations). Julia Paxson has collaborated with scholars based in United States and Croatia. Frequent co-authors include Edward P. Ingenito, Andrew M. Hoffman, Melissa R. Mazan, Airiel M. Davis, Alisha M. Gruntman, Shivraj Tyagi, Norton Ja, Kangla Tsung, Andrew M. Hoffman and David W. Ramey. Their work appears in journals such as PLoS ONE, Stem Cells and Development, Journal of Visualized Experiments, Journal of Veterinary Emergency and Critical Care and Journal of Veterinary Pharmacology and Therapeutics.

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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