Michael Shires

22 papers receiving 620 citations

Peers

Michael Shires
Comparison fields: 5 of 88
  • Endocrinology, Diabetes and Metabolism 156
  • Microbiology 6
  • Pediatrics, Perinatology and Child Health 114
  • Biophysics 29
  • Public Health, Environmental and Occupational Health 129
Replace Hong‐Mei Xiao with:
Hong‐Mei Xiao China
Esther Sutter Switzerland
Michael D. Ober United States
Colin G. Blackmore United Kingdom
Makoto Takayama Japan
Sarah Eckenrode United States
Mindy L. Rawlins United States
Xiaolong Cheng China
Giuliana Cortese Italy
Jonathan J. Edwards United States
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Citations per field
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Citations per year

Countries citing papers authored by Michael Shires

Since Specialization
Citations

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

Fields of papers citing papers by Michael Shires

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011191
2 2009150
3
Colour Normalisation in Digital Histopathology Images
2009100
4 201043
5 199120
6 201916
7
Expression pattern of FGFR2, Grb2 and Plcγ1 acts as a novel prognostic marker of recurrence recurrence-free survival in lung adenocarcinoma.
201516
8 201712
9 202011
10 200910
11 20047
12 20236
13 20196
14 19886
15 20196
16 19866
17 20036
18 19855
19 20094
20 19843

About Michael Shires

Michael Shires is a scholar working on Molecular Biology, Surgery, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 22 papers that have together received 628 indexed citations. Recurring topics across this work include AI in cancer detection (3 papers), Organ Transplantation Techniques and Outcomes (3 papers), Chronic Kidney Disease and Diabetes (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Cell Image Analysis Techniques (2 papers), Laser Applications in Dentistry and Medicine (2 papers), Diet, Metabolism, and Disease (2 papers) and Plant and Fungal Interactions Research (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (156 citations), Microbiology (6 citations), Pediatrics, Perinatology and Child Health (114 citations), Biophysics (29 citations) and Public Health, Environmental and Occupational Health (129 citations). Michael Shires has collaborated with scholars based in United Kingdom, United States and Malaysia. Frequent co-authors include Bruce E. Hayward, Ian Carr, David T. Bonthron, Christine P. Diggle, D. Crellin, Aruna Asipu, Alex Markham, Derek Leitch, Darren Treanor and Philip Quirke. Their work appears in journals such as Journal of Histochemistry & Cytochemistry, The Journal of Pathology, Scientific Reports, Journal of Biophotonics and Laboratory Animals.

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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