James T. Case

55 papers receiving 1.7k citations

Peers

James T. Case
Comparison fields: 5 of 144
  • Equine 592
  • Health Information Management 129
  • Orthopedics and Sports Medicine 172
  • Small Animals 149
  • Agronomy and Crop Science 128
Replace R. van den Hoven with:
R. van den Hoven Austria
Francesca Bonelli Italy
L. Bonizzi Italy
David J. Platt United Kingdom
Hannah Wood United Kingdom
Bryn Tennant United Kingdom
James E. C. Bellamy Canada
Kathrin Herzog Germany
Sarah Parker Canada
José L. Gonzáles Netherlands
James T. Case relative to R. van den Hoven Austria R. van den Hoven's profile →
Citations per field
00.5×3.4×
R. van den Hoven · 1×
Citations per year

Countries citing papers authored by James T. Case

Since Specialization
Citations

This map shows the geographic impact of James T. Case'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 James T. Case with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James T. Case more than expected).

Fields of papers citing papers by James T. Case

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James T. Case. 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 James T. Case. The network helps show where James T. Case may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003427
2 1996126
3 201096
4 199893
5 199891
6 199683
7 198179
8 199579
9 200276
10 201148
11 201647
12 201445
13 199139
14 199636
15 201236
16 199235
17 201433
18 200633
19
Optimization of parameters for detecting antibodies against infectious bronchitis virus using an enzyme-linked immunosorbent assay: temporal response to vaccination and challenge with live virus.
198333
20 199829

About James T. Case

James T. Case is a scholar working on Molecular Biology, Equine, Genetics, Agronomy and Crop Science and Artificial Intelligence, having authored 61 papers that have together received 1.8k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (13 papers), Veterinary Equine Medical Research (11 papers), Viral gastroenteritis research and epidemiology (4 papers), Salmonella and Campylobacter epidemiology (4 papers), Semantic Web and Ontologies (4 papers), Animal Virus Infections Studies (4 papers), Animal Disease Management and Epidemiology (4 papers) and Escherichia coli research studies (3 papers). The work is most often cited by research in Equine (592 citations), Health Information Management (129 citations), Orthopedics and Sports Medicine (172 citations), Small Animals (149 citations) and Agronomy and Crop Science (128 citations). James T. Case has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Alex Ardans, Susan M. Stover, Ian A. Gardner, Bill Johnson, Douglas C. Wallace, Deryck H. Read, Hailu Kinde, J. N. Hook, Arden W. Forrey and Raymond D. Aller. Their work appears in journals such as Journal of Veterinary Diagnostic Investigation, Journal of the American Veterinary Medical Association, American Journal of Veterinary Research, Journal of the American Medical Informatics Association and Avian 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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