Mark Chaffin
- Molecular Biology top 5%
- Genetics top 1%
- Cardiology and Cardiovascular Medicine top 2%
- Surgery top 10%
- Physiology top 10%
- Co-authors
- Patrick T. EllinorAmit V. KheraSekar KathiresanKrishna G. AragamSeung Hoan ChoiCarolina RoselliEric S. LanderMary E. Haas
- Topics
- Genetic Associations and Epidemiology (12 papers)Single-cell and spatial transcriptomics (6 papers)Cardiomyopathy and Myosin Studies (3 papers)
- Journals
- NatureCellCirculation
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Mark Chaffin
30 papers receiving 4.1k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Molecular Biology 1.5k
- Genetics 1.5k
- Cardiology and Cardiovascular Medicine 862
- Surgery 454
- Physiology 346
Countries citing papers authored by Mark Chaffin
This map shows the geographic impact of Mark Chaffin'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 Mark Chaffin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Chaffin more than expected).
Fields of papers citing papers by Mark Chaffin
This network shows the impact of papers produced by Mark Chaffin. 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 Mark Chaffin. The network helps show where Mark Chaffin may publish in the future.
Co-authorship network of co-authors of Mark Chaffin
This figure shows the co-authorship network connecting the top 25 collaborators of Mark Chaffin. A scholar is included among the top collaborators of Mark Chaffin 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 Mark Chaffin. Mark Chaffin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 38 | |
| 3 | 18 | |
| 4 | 14 | |
| 5 | Transfer learning enables predictions in network biologybreakdown → | 383 |
| 6 | 3 | |
| 7 | Single-nucleus profiling of human dilated and hypertrophic cardiomyopathybreakdown → | 180 |
| 8 | 10 | |
| 9 | Transcriptional and Cellular Diversity of the Human Heartbreakdown → | 332 |
| 10 | 129 | |
| 11 | 68 | |
| 12 | Abstract 16565: Integration Of A Genome-wide Polygenic Score With ACC/AHA Pooled Cohorts Equation In Prediction Of Coronary Artery Disease Events In >285,000 Participants | 3 |
| 13 | 3 | |
| 14 | Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthoodbreakdown → | 432 |
| 15 | Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutationsbreakdown → | 1631 |
| 16 | 4 | |
| 17 | Genetics of blood lipids among similar to 300,000 multi-ethnic participants of the Million Veteran Program | 0 |
| 18 | 150 | |
| 19 | 60 | |
| 20 | 66 |
About Mark Chaffin
Mark Chaffin is a scholar working on Equine, Genetics and Cardiology and Cardiovascular Medicine, having authored 31 papers that have together received 4.1k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (12 papers), Single-cell and spatial transcriptomics (6 papers) and Cardiomyopathy and Myosin Studies (3 papers). The work is most often cited by research in Genetics (1.5k citations), Equine (64 citations) and Cardiology and Cardiovascular Medicine (862 citations). Mark Chaffin has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Patrick T. Ellinor, Amit V. Khera, Sekar Kathiresan, Krishna G. Aragam, Seung Hoan Choi, Carolina Roselli, Eric S. Lander, Mary E. Haas, Steven A. Lubitz and Pradeep Natarajan. Their work appears in journals such as Nature, Cell and Circulation.
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.