David R. Crosslin
- Molecular Biology top 10%
- Genetics top 5%
- Physiology top 5%
- Epidemiology top 10%
- Cardiology and Cardiovascular Medicine top 5%
- Co-authors
- Svati H. ShahCarol HaynesElizabeth R. HauserWilliam E. KrausGail P. JarvikSarah C. NelsonJames R. BainMichael J. Muehlbauer
- Topics
- Genetic Associations and Epidemiology (17 papers)Genomics and Rare Diseases (7 papers)BRCA gene mutations in cancer (6 papers)
- Partner nations
- United StatesUnited KingdomNew Zealand
In The Last Decade
David R. Crosslin
62 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 145
- Molecular Biology 1.1k
- Genetics 609
- Physiology 433
- Epidemiology 372
- Cardiology and Cardiovascular Medicine 307
Countries citing papers authored by David R. Crosslin
This map shows the geographic impact of David R. Crosslin'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 David R. Crosslin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David R. Crosslin more than expected).
Fields of papers citing papers by David R. Crosslin
This network shows the impact of papers produced by David R. Crosslin. 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 David R. Crosslin. The network helps show where David R. Crosslin may publish in the future.
Co-authorship network of co-authors of David R. Crosslin
This figure shows the co-authorship network connecting the top 25 collaborators of David R. Crosslin. A scholar is included among the top collaborators of David R. Crosslin 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 David R. Crosslin. David R. Crosslin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 6 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 9 | |
| 6 | 56 | |
| 7 | 50 | |
| 8 | 75 | |
| 9 | 98 | |
| 10 | 10 | |
| 11 | 280 | |
| 12 | 44 | |
| 13 | 216 | |
| 14 | 3 | |
| 15 | 35 | |
| 16 | Abstract 1261: Plasma Metabolomic Profiles Predict Future Cardiovascular Events | 1 |
| 17 | 46 | |
| 18 | 18 | |
| 19 | Developing a framework for conducting economic evaluations of community-based health information technology interventions. | 1 |
| 20 | Assessing the potential economic value of health information technology interventions in a community-based health network. | 3 |
About David R. Crosslin
David R. Crosslin is a scholar working on Genetics, Health Information Management and Cancer Research, having authored 64 papers that have together received 2.4k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (17 papers), Genomics and Rare Diseases (7 papers) and BRCA gene mutations in cancer (6 papers). The work is most often cited by research in Genetics (609 citations), Physiology (433 citations) and Health Information Management (76 citations). David R. Crosslin has collaborated with scholars based in United States, United Kingdom and New Zealand. Frequent co-authors include Svati H. Shah, Carol Haynes, Elizabeth R. Hauser, William E. Kraus, Gail P. Jarvik, Sarah C. Nelson, James R. Bain, Michael J. Muehlbauer, Christopher B. Newgard and Geoffrey S. Ginsburg. Their work appears in journals such as Circulation, Nature Communications and Bioinformatics.
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.