Keith P. Ray

2.8k citations
53 papers · 2.3k indexed · h-index 22

Impact in

  • Aging top 1%
    • Genetics, Aging, and Longevity in Model Organisms
  • Immunology top 2%
    • Immune Response and Inflammation
    • Invertebrate Immune Response Mechanisms
    • interferon and immune responses

Papers in

Keith P. Ray

52 papers receiving 2.2k citations

Peers

Keith P. Ray
Comparison fields: 5 of 114
  • Aging 197
  • Immunology 1.1k
  • Microbiology 150
  • Cancer Research 334
  • Insect Science 221
Replace Daniel Wong with:
Daniel Wong United Kingdom
Cliff J. Luke United States
Akiko Shiratsuchi Japan
Xavier Préville France
Yair Argon United States
Martha J. Larsen United States
David F. Stojdl Canada
T Maniatis United States
Gisela Heidecker United States
Keith P. Ray relative to Daniel Wong United Kingdom Daniel Wong's profile →
Citations per field
00.5×5.2×
Daniel Wong · 1×
Citations per year

Countries citing papers authored by Keith P. Ray

Since Specialization
Citations

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

Fields of papers citing papers by Keith P. Ray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keith P. Ray. 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 Keith P. Ray. The network helps show where Keith P. Ray may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202123
2 201848
3 20142
4 20141
5 201018
6 201034
7 201061
8 20062
9 200644
10 200624
11 2003348
12 20023
13 200131
14 2001336
15 200110
16 20009
17 199744
18 199619
19 198811
20
Contextual architecture : responding to existing style
19807

About Keith P. Ray

Keith P. Ray is a scholar working on Aging, Behavioral Neuroscience, Immunology and Allergy, Immunology and Endocrinology, Diabetes and Metabolism, having authored 53 papers that have together received 2.3k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (12 papers), Immune Response and Inflammation (9 papers), NF-κB Signaling Pathways (7 papers), Cell Adhesion Molecules Research (5 papers), Cytokine Signaling Pathways and Interactions (5 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Stress Responses and Cortisol (4 papers) and Inflammatory Bowel Disease (4 papers). The work is most often cited by research in Aging (197 citations), Immunology (1.1k citations), Microbiology (150 citations), Cancer Research (334 citations) and Insect Science (221 citations). Keith P. Ray has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Filippo Volpe, Barbara Maschera, Kimberly Burns, P. England, Michael Wallis, Chris Plumpton, Mary A. Morse, Fabio Martinon, J Tschopp and Alan J. Lewis. Their work appears in journals such as Molecular and Cellular Endocrinology, FEBS Letters, Biochemical Journal, Biochemical Society Transactions and Scientific Reports.

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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