Jeff Boyle

689 citations
12 papers · 499 · h-index 11

Impact in

  • Immunology top 10%
    • Immunotherapy and Immune Responses
    • Immune Response and Inflammation
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Benford’s Law and Fraud Detection

Papers in

Jeff Boyle

12 papers receiving 485 citations

Peers

Jeff Boyle
Comparison fields: 5 of 92
  • Immunology 255
  • Statistics and Probability 54
  • Virology 18
  • Obstetrics and Gynecology 24
  • Epidemiology 75
Replace Sheldon D. Weed with:
Sheldon D. Weed United States
Gourab Mukherjee United States
Samuel Pine United States
Anthony Bowen United States
Gerald Downey United Kingdom
Dean Follmann United States
Benjamin A. Kruskal United States
Bronner P. Gonçalves United Kingdom
Moses Baisor Papua New Guinea
Jeff Boyle relative to Sheldon D. Weed United States Sheldon D. Weed's profile →
Citations per field
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Sheldon D. Weed · 1×
Citations per year

Countries citing papers authored by Jeff Boyle

Since Specialization
Citations

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

Fields of papers citing papers by Jeff Boyle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 200795
2 201186
3 200778
4 200953
5
Supplementary Figure 2
201145
6 199441
7 200637
8 199619
9 199417
10 199614
11 201110
12 19844

About Jeff Boyle

Jeff Boyle is a scholar working on Immunology, Molecular Biology, Algebra and Number Theory, Computational Theory and Mathematics and Obstetrics and Gynecology, having authored 12 papers that have together received 499 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (5 papers), semigroups and automata theory (2 papers), Analytic Number Theory Research (2 papers), T-cell and B-cell Immunology (2 papers), Cardiovascular Issues in Pregnancy (1 paper), Gestational Diabetes Research and Management (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper) and Benford’s Law and Fraud Detection (1 paper). The work is most often cited by research in Immunology (255 citations), Statistics and Probability (54 citations), Virology (18 citations), Obstetrics and Gynecology (24 citations) and Epidemiology (75 citations). Jeff Boyle has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Eugene Maraskovsky, Debbie Drane, Charmaine Gittleson, Gabrielle T. Belz, Nicholas S. Wilson, Nick Wilson, Neil C. Robson, Max Schnurr, Stefanie Loeser and Phil Hass. Their work appears in journals such as Immunology and Cell Biology, Biochimica et Biophysica Acta (BBA) - General Subjects, Obstetrical & Gynecological Survey, Expert Review of Vaccines and Obstetrics and Gynecology.

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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