Daphna Weissglas‐Volkov
- Molecular Biology
- Genetics top 10%
- Cardiology and Cardiovascular Medicine top 5%
- Surgery top 10%
- Endocrinology, Diabetes and Metabolism top 5%
- Co-authors
- Päivi PajukantaNoam ShomronEitan FriedmanTeresa Tusié‐LunaCarlos A. Aguilar‐SalinasJanet S. SinsheimerNatalie ArtziJoão Conde
- Topics
- Genetic Associations and Epidemiology (10 papers)Lipid metabolism and disorders (8 papers)Lipoproteins and Cardiovascular Health (6 papers)
- Cited by
- Cancer ResearchEndocrinology, Diabetes and MetabolismCardiology and Cardiovascular Medicine
- Partner nations
- United StatesIsraelFinland
In The Last Decade
Daphna Weissglas‐Volkov
34 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 102
- Molecular Biology 496
- Genetics 320
- Cardiology and Cardiovascular Medicine 311
- Surgery 306
- Endocrinology, Diabetes and Metabolism 299
Countries citing papers authored by Daphna Weissglas‐Volkov
This map shows the geographic impact of Daphna Weissglas‐Volkov'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 Daphna Weissglas‐Volkov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daphna Weissglas‐Volkov more than expected).
Fields of papers citing papers by Daphna Weissglas‐Volkov
This network shows the impact of papers produced by Daphna Weissglas‐Volkov. 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 Daphna Weissglas‐Volkov. The network helps show where Daphna Weissglas‐Volkov may publish in the future.
Co-authorship network of co-authors of Daphna Weissglas‐Volkov
This figure shows the co-authorship network connecting the top 25 collaborators of Daphna Weissglas‐Volkov. A scholar is included among the top collaborators of Daphna Weissglas‐Volkov 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 Daphna Weissglas‐Volkov. Daphna Weissglas‐Volkov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 26 | |
| 5 | 40 | |
| 6 | 4 | |
| 7 | Local microRNA delivery targets Palladin and prevents metastatic breast cancer | 1 |
| 8 | 2 | |
| 9 | 22 | |
| 10 | 136 | |
| 11 | 13 | |
| 12 | 95 | |
| 13 | 24 | |
| 14 | 15 | |
| 15 | 29 | |
| 16 | 51 | |
| 17 | 12 | |
| 18 | 165 | |
| 19 | 46 | |
| 20 | 162 |
About Daphna Weissglas‐Volkov
Daphna Weissglas‐Volkov is a scholar working on Genetics, Cancer Research and Biochemistry, having authored 34 papers that have together received 1.3k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (10 papers), Lipid metabolism and disorders (8 papers) and Lipoproteins and Cardiovascular Health (6 papers). The work is most often cited by research in Cancer Research (273 citations), Endocrinology, Diabetes and Metabolism (299 citations) and Cardiology and Cardiovascular Medicine (311 citations). Daphna Weissglas‐Volkov has collaborated with scholars based in United States, Israel and Finland. Frequent co-authors include Päivi Pajukanta, Noam Shomron, Eitan Friedman, Teresa Tusié‐Luna, Carlos A. Aguilar‐Salinas, Janet S. Sinsheimer, Natalie Artzi, João Conde, Avital Gilam and Nuria Oliva. Their work appears in journals such as Nature, Journal of Clinical Investigation and Nature Communications.
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.