Matthew G. Johnson
- Endocrinology, Diabetes and Metabolism top 5%
- Epidemiology top 10%
- Surgery
- Cardiology and Cardiovascular Medicine top 10%
- Infectious Diseases top 10%
- Co-authors
- Jason E. StoutPeter C. O’BrienHartzell V. SchaffGunjan Y. GandhiMartin AbelCharles J. MullanyRobert A. RizzaGregory A. Nuttall
- Topics
- Antibiotics Pharmacokinetics and Efficacy (12 papers)Antibiotic Resistance in Bacteria (10 papers)SARS-CoV-2 and COVID-19 Research (7 papers)
- Cited by
- Applied Microbiology and BiotechnologyMolecular MedicineEndocrinology, Diabetes and Metabolism
- Journals
- SHILAP Revista de lepidopterologíaAnnals of Internal MedicineApplied and Environmental Microbiology
- Partner nations
- United StatesFranceGreece
In The Last Decade
Matthew G. Johnson
34 papers receiving 934 citations
Peers
Comparison fields: 5 of 95
- Endocrinology, Diabetes and Metabolism 302
- Epidemiology 292
- Surgery 233
- Cardiology and Cardiovascular Medicine 157
- Infectious Diseases 146
Countries citing papers authored by Matthew G. Johnson
This map shows the geographic impact of Matthew G. Johnson'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 Matthew G. Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew G. Johnson more than expected).
Fields of papers citing papers by Matthew G. Johnson
This network shows the impact of papers produced by Matthew G. Johnson. 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 Matthew G. Johnson. The network helps show where Matthew G. Johnson may publish in the future.
Co-authorship network of co-authors of Matthew G. Johnson
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew G. Johnson. A scholar is included among the top collaborators of Matthew G. Johnson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthew G. Johnson. Matthew G. Johnson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 9 | |
| 4 | 5 | |
| 5 | 23 | |
| 6 | 3 | |
| 7 | 6 | |
| 8 | 44 | |
| 9 | 15 | |
| 10 | 6 | |
| 11 | 13 | |
| 12 | 13 | |
| 13 | 92 | |
| 14 | 31 | |
| 15 | 7 | |
| 16 | 28 | |
| 17 | 59 | |
| 18 | 55 | |
| 19 | 12 | |
| 20 | 3 |
About Matthew G. Johnson
Matthew G. Johnson is a scholar working on Molecular Medicine, Applied Microbiology and Biotechnology and Pharmacology, having authored 36 papers that have together received 960 indexed citations. Recurring topics across this work include Antibiotics Pharmacokinetics and Efficacy (12 papers), Antibiotic Resistance in Bacteria (10 papers) and SARS-CoV-2 and COVID-19 Research (7 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (49 citations), Molecular Medicine (114 citations) and Endocrinology, Diabetes and Metabolism (302 citations). Matthew G. Johnson has collaborated with scholars based in United States, France and Greece. Frequent co-authors include Jason E. Stout, Peter C. O’Brien, Hartzell V. Schaff, Gunjan Y. Gandhi, Martin Abel, Charles J. Mullany, Robert A. Rizza, Gregory A. Nuttall, Susanne M. Cutshall and Arthur Robin Williams. Their work appears in journals such as SHILAP Revista de lepidopterología, Annals of Internal Medicine and Applied and Environmental Microbiology.
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.