Michael G. Casey

760 citations
24 papers · 588 · h-index 14

Impact in

Papers in

    • Probiotics and Fermented Foods 18
    • Protein Hydrolysis and Bioactive Peptides 5
    • Genomics and Phylogenetic Studies 3

Michael G. Casey

23 papers receiving 551 citations

Peers

Michael G. Casey
Comparison fields: 5 of 78
  • Food Science 351
  • Animal Science and Zoology 96
  • Agronomy and Crop Science 90
  • Biotechnology 59
  • Microbiology 41
Replace J.L. Bergere with:
J.L. Bergere France
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Giuseppina Cacace Italy
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Citations per field
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Citations per year

Countries citing papers authored by Michael G. Casey

Since Specialization
Citations

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

Fields of papers citing papers by Michael G. Casey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael G. Casey. 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 Michael G. Casey. The network helps show where Michael G. Casey may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200782
2 200271
3 198571
4 200248
5 200243
6 200538
7 199934
8 200431
9 200426
10 200624
11 200421
12 200315
13 200014
14 199914
15 198410
16 20027
17 20087
18 19996
19 19976
20
Application of Samuelson - Stone linear expenditure system to food consumption in Ireland
19735

About Michael G. Casey

Michael G. Casey is a scholar working on Food Science, Molecular Biology, Agronomy and Crop Science, Ecology and Cellular and Molecular Neuroscience, having authored 24 papers that have together received 588 indexed citations. Recurring topics across this work include Probiotics and Fermented Foods (18 papers), Milk Quality and Mastitis in Dairy Cows (7 papers), Protein Hydrolysis and Bioactive Peptides (5 papers), Genomics and Phylogenetic Studies (3 papers), Bacteriophages and microbial interactions (3 papers), Neuropeptides and Animal Physiology (3 papers), Meat and Animal Product Quality (3 papers) and Peptidase Inhibition and Analysis (3 papers). The work is most often cited by research in Food Science (351 citations), Animal Science and Zoology (96 citations), Agronomy and Crop Science (90 citations), Biotechnology (59 citations) and Microbiology (41 citations). Michael G. Casey has collaborated with scholars based in Switzerland, Ireland and Germany. Frequent co-authors include Jacques Meyer, Marie‐Therese Fröhlich‐Wyder, W. Schaeren, H Bachmann, J. Naskova, H.U. Graber, A. Steiner, J.O. Bosset, René Badertscher and J Meyer. Their work appears in journals such as LWT, Digestion, International Dairy Journal, Journal of Dairy Science and European Food Research and Technology.

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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