Dana C. Crawford
- Genetics top 0.5%
- Molecular Biology top 5%
- Pharmacology top 0.2%
- Cognitive Neuroscience top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Co-authors
- Deborah A. NickersonMarylyn D. RitchieStephanie L. ShermanJoshua C. DennyJuan AcuñaDan M. RodenJill M. PulleyKristin Brown‐Gentry
- Topics
- Genetic Associations and Epidemiology (76 papers)Genomics and Rare Diseases (19 papers)Pharmacogenetics and Drug Metabolism (13 papers)
- Journals
- CirculationNature GeneticsBlood
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Dana C. Crawford
145 papers receiving 5.8k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Genetics 2.9k
- Molecular Biology 2.1k
- Pharmacology 741
- Cognitive Neuroscience 643
- Cardiology and Cardiovascular Medicine 504
Countries citing papers authored by Dana C. Crawford
This map shows the geographic impact of Dana C. Crawford'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 Dana C. Crawford with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dana C. Crawford more than expected).
Fields of papers citing papers by Dana C. Crawford
This network shows the impact of papers produced by Dana C. Crawford. 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 Dana C. Crawford. The network helps show where Dana C. Crawford may publish in the future.
Co-authorship network of co-authors of Dana C. Crawford
This figure shows the co-authorship network connecting the top 25 collaborators of Dana C. Crawford. A scholar is included among the top collaborators of Dana C. Crawford 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 Dana C. Crawford. Dana C. Crawford 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 | 7 | |
| 3 | 0 | |
| 4 | POAG genetic risk score performs worse in African-descent than European-descent samples, highlighting need for expanded genetic studies in diverse populations | 0 |
| 5 | 7 | |
| 6 | 16 | |
| 7 | 7 | |
| 8 | Improving access to socioeconomic data for genetic studies of racial health disparities | 1 |
| 9 | PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associationsbreakdown → | 703 |
| 10 | 76 | |
| 11 | 9 | |
| 12 | 3 | |
| 13 | 4 | |
| 14 | 5 | |
| 15 | 4 | |
| 16 | 22 | |
| 17 | 144 | |
| 18 | 53 | |
| 19 | 59 | |
| 20 | 6 |
About Dana C. Crawford
Dana C. Crawford is a scholar working on Genetics, Pharmacology and Endocrinology, Diabetes and Metabolism, having authored 151 papers that have together received 5.9k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (76 papers), Genomics and Rare Diseases (19 papers) and Pharmacogenetics and Drug Metabolism (13 papers). The work is most often cited by research in Genetics (2.9k citations), Pharmacology (741 citations) and Health Information Management (183 citations). Dana C. Crawford has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Deborah A. Nickerson, Marylyn D. Ritchie, Stephanie L. Sherman, Joshua C. Denny, Juan Acuña, Dan M. Roden, Jill M. Pulley, Kristin Brown‐Gentry, Melissa Basford and Mark J. Rieder. Their work appears in journals such as Circulation, Nature Genetics and Blood.
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.