Kay Rasmussen

657 citations
9 papers · 566 · h-index 9

Impact in

  • Genetics top 10%
    • Estrogen and related hormone effects
    • Genetic Syndromes and Imprinting
    • Kruppel-like factors research
    • TGF-β signaling in diseases
    • Bone Metabolism and Diseases
    • Cancer-related gene regulation

Papers in

    • Estrogen and related hormone effects 4
    • Animal Genetics and Reproduction 2
    • TGF-β signaling in diseases 3
    • Bone Metabolism and Diseases 3

Kay Rasmussen

9 papers receiving 557 citations

Peers

Kay Rasmussen
Comparison fields: 5 of 67
  • Genetics 191
  • Molecular Biology 402
  • Reproductive Medicine 42
  • Orthopedics and Sports Medicine 39
  • Oncology 96
Replace Anne-Marie Hedge with:
Anne-Marie Hedge United States
Benjamin H. Mullin Australia
James Farris United States
A. T. Holder United Kingdom
Jennifer A. Kennell United States
Jeong Soo Hong South Korea
GE-MING LUI United States
Fernándo Rodríguez Chile
Kenta Kishimoto Japan
Kay Rasmussen relative to Anne-Marie Hedge United States Anne-Marie Hedge's profile →
Citations per field
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Citations per year

Countries citing papers authored by Kay Rasmussen

Since Specialization
Citations

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

Fields of papers citing papers by Kay Rasmussen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Kay Rasmussen, 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 Kay Rasmussen Line = papers co-authored together Kay Rasmussen links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 1995228
2 200599
3 199283
4 198437
5 199527
6 199026
7 198623
8 199123
9 199320

About Kay Rasmussen

Kay Rasmussen is a scholar working on Genetics, Molecular Biology, Animal Science and Zoology, Oncology and Pathology and Forensic Medicine, having authored 9 papers that have together received 566 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (4 papers), TGF-β signaling in diseases (3 papers), Bone Metabolism and Diseases (3 papers), Animal Nutrition and Physiology (2 papers), Bone health and treatments (2 papers), Animal Genetics and Reproduction (2 papers), Neurobiology and Insect Physiology Research (1 paper) and Insect and Pesticide Research (1 paper). The work is most often cited by research in Genetics (191 citations), Molecular Biology (402 citations), Reproductive Medicine (42 citations), Orthopedics and Sports Medicine (39 citations) and Oncology (96 citations). Kay Rasmussen has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Malayannan Subramaniam, Thomas C. Spelsberg, B. Lawrence Riggs, Merry Jo Oursler, Steven A. Harris, T. C. Spelsberg, Douglas S. Colvard, Philip E. Keeting, David G. Monroe and David J. Rickard. Their work appears in journals such as Endocrinology, Journal of Cellular Biochemistry, Nucleic Acids Research, Proceedings of the National Academy of Sciences and Molecular and Cellular 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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