Ryan J Paxman

1.0k citations
10 papers · 703 indexed · h-index 9

Impact in

    • Endoplasmic Reticulum Stress and Disease
    • Cellular transport and secretion
  • Aging top 10%

Papers in

    • Genetics, Aging, and Longevity in Model Organisms 3
    • Endoplasmic Reticulum Stress and Disease 7

Ryan J Paxman

10 papers receiving 700 citations

Peers

Ryan J Paxman
Comparison fields: 5 of 79
  • Cell Biology 427
  • Aging 20
  • Molecular Biology 407
  • Epidemiology 182
  • Biotechnology 39
Replace Patricia G. Tu with:
Patricia G. Tu United States
Anouk Emadali France
Wen‐An Wang Canada
Peter Kreuzaler United Kingdom
Huadong Pei China
Jasper H.L. Claessen United States
Yuh-Ying Yeh United States
Padmaja Gade United States
Carson A. Wills United States
Ryan J Paxman relative to Patricia G. Tu United States Patricia G. Tu's profile →
Citations per field
00.5×3.3×
Patricia G. Tu · 1×
Citations per year

Countries citing papers authored by Ryan J Paxman

Since Specialization
Citations

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

Fields of papers citing papers by Ryan J Paxman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan J Paxman. 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 Ryan J Paxman. The network helps show where Ryan J Paxman may publish in the future.

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 20234
2 202118
3 202031
4 2020109
5 2019144
6 201856
7 201881
8 2016173
9 201439
10 201448

About Ryan J Paxman

Ryan J Paxman is a scholar working on Aging, Cell Biology, Epidemiology, Biotechnology and Genetics, having authored 10 papers that have together received 703 indexed citations. Recurring topics across this work include Endoplasmic Reticulum Stress and Disease (7 papers), Autophagy in Disease and Therapy (4 papers), Pancreatic function and diabetes (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), Signaling Pathways in Disease (2 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (2 papers), Biochemical and Structural Characterization (1 paper) and Protein Kinase Regulation and GTPase Signaling (1 paper). The work is most often cited by research in Cell Biology (427 citations), Aging (20 citations), Molecular Biology (407 citations), Epidemiology (182 citations) and Biotechnology (39 citations). Ryan J Paxman has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Jeffery W. Kelly, R. Luke Wiseman, Lars Plate, Evan T. Powers, Erik A. Blackwood, Donna J. Thuerauf, Christina B. Cooley, Timothy Spicer, Khalid Azizi and Louis Scampavia. Their work appears in journals such as eLife, Journal of the American Chemical Society, Amyloid, Nature Communications and Nature Chemical Biology.

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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