Matthew R. Ban
- Surgery top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Endocrinology, Diabetes and Metabolism top 2%
- Molecular Biology
- Genetics top 5%
- Co-authors
- Robert A. HegeleHenian CaoJian WangMurray W. HuffRebecca L. PollexAdam D. McIntyreSalim YusufSonia S. Anand
- Topics
- Lipoproteins and Cardiovascular Health (18 papers)Lipid metabolism and disorders (14 papers)Cancer, Lipids, and Metabolism (12 papers)
- Cited by
- Endocrinology, Diabetes and MetabolismCardiology and Cardiovascular MedicineCancer Research
- Partner nations
- CanadaUnited StatesDenmark
In The Last Decade
Matthew R. Ban
44 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 85
- Surgery 803
- Cardiology and Cardiovascular Medicine 634
- Endocrinology, Diabetes and Metabolism 525
- Molecular Biology 476
- Genetics 410
Countries citing papers authored by Matthew R. Ban
This map shows the geographic impact of Matthew R. Ban'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 R. Ban with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew R. Ban more than expected).
Fields of papers citing papers by Matthew R. Ban
This network shows the impact of papers produced by Matthew R. Ban. 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 R. Ban. The network helps show where Matthew R. Ban may publish in the future.
Co-authorship network of co-authors of Matthew R. Ban
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew R. Ban. A scholar is included among the top collaborators of Matthew R. Ban 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 R. Ban. Matthew R. Ban is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 54 | |
| 2 | 11 | |
| 3 | 4 | |
| 4 | 47 | |
| 5 | 14 | |
| 6 | 10 | |
| 7 | 79 | |
| 8 | 19 | |
| 9 | 1 | |
| 10 | 9 | |
| 11 | 4 | |
| 12 | 74 | |
| 13 | 95 | |
| 14 | 48 | |
| 15 | 32 | |
| 16 | 111 | |
| 17 | 64 | |
| 18 | 44 | |
| 19 | 22 | |
| 20 | 10 |
About Matthew R. Ban
Matthew R. Ban is a scholar working on Endocrinology, Diabetes and Metabolism, Cancer Research and Cardiology and Cardiovascular Medicine, having authored 44 papers that have together received 1.7k indexed citations. Recurring topics across this work include Lipoproteins and Cardiovascular Health (18 papers), Lipid metabolism and disorders (14 papers) and Cancer, Lipids, and Metabolism (12 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (525 citations), Cardiology and Cardiovascular Medicine (634 citations) and Cancer Research (302 citations). Matthew R. Ban has collaborated with scholars based in Canada, United States and Denmark. Frequent co-authors include Robert A. Hegele, Henian Cao, Jian Wang, Murray W. Huff, Rebecca L. Pollex, Adam D. McIntyre, Salim Yusuf, Sonia S. Anand, John F. Robinson and Brooke A. Miskie. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Stroke and Kidney International.
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.