Jennifer MacGregor

830 citations
8 papers · 677 · h-index 6

Impact in

  • Oncology top 10%
    • Cancer Cells and Metastasis
    • Pancreatic and Hepatic Oncology Research
    • Cell Adhesion Molecules Research

Papers in

    • Data-Driven Disease Surveillance 2
    • Herpesvirus Infections and Treatments 2
    • Virology and Viral Diseases 1
    • TGF-β signaling in diseases 2
    • Cancer-related gene regulation 2
    • Viral Infectious Diseases and Gene Expression in Insects 1

Jennifer MacGregor

8 papers receiving 663 citations

Peers

Jennifer MacGregor
Comparison fields: 5 of 55
  • Oncology 354
  • Immunology and Allergy 37
  • Molecular Biology 446
  • Cancer Research 80
  • Biotechnology 36
Replace Fumitaka Numa with:
Fumitaka Numa Japan
Tine S. Mantoni United Kingdom
Tuomo Alanko Finland
RE Hawkins United Kingdom
Daniel R. Vlock United States
Anju Gupta India
Jun‐ichi Tanuma Japan
Mee-Sook Roh South Korea
Esperanza Feijoó Spain
Clay Davis United States
Jennifer MacGregor relative to Fumitaka Numa Japan Fumitaka Numa's profile →
Citations per field
00.5×2.9×
Fumitaka Numa · 1×
Citations per year

Countries citing papers authored by Jennifer MacGregor

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer MacGregor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

8 of 8 papers shown
#Work
1 2002306
2 2002279
3 200156
4 202016
5 20176
6 20086
7 20215
8 20173

About Jennifer MacGregor

Jennifer MacGregor is a scholar working on Epidemiology, Molecular Biology, Infectious Diseases, Oncology and Health, having authored 8 papers that have together received 677 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (2 papers), TGF-β signaling in diseases (2 papers), Cancer Cells and Metastasis (2 papers), Cancer-related gene regulation (2 papers), Herpesvirus Infections and Treatments (2 papers), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Vaccine Coverage and Hesitancy (1 paper) and Virology and Viral Diseases (1 paper). The work is most often cited by research in Oncology (354 citations), Immunology and Allergy (37 citations), Molecular Biology (446 citations), Cancer Research (80 citations) and Biotechnology (36 citations). Jennifer MacGregor has collaborated with scholars based in United States. Frequent co-authors include Glenn Merlino, Lalage M. Wakefield, Jeffrey Green, Miriam R. Anver, Binwu Tang, John J. Letterio, Oksana I. Dukhanina, Mizuko Mamura, Zi-yao Liu and Yu-an Yang. Their work appears in journals such as Journal of Clinical Investigation, American Journal of Public Health, MMWR Morbidity and Mortality Weekly Report, Clinical Infectious Diseases and Sexually Transmitted Diseases.

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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