Philip Beineke
- Molecular Biology
- Artificial Intelligence top 10%
- Hepatology top 10%
- Cardiology and Cardiovascular Medicine
- Epidemiology
- Co-authors
- Gary W. WitherellTrevor HastieShivakumar VaithyanathanSteven RosenbergMichael ElashoffJames A. WingroveWilliam E. KrausHeng Tao
- Topics
- Molecular Biology Techniques and Applications (4 papers)Histiocytic Disorders and Treatments (3 papers)Viral-associated cancers and disorders (3 papers)
- Journals
- Nature CommunicationsJournal of Clinical OncologySHILAP Revista de lepidopterología
- Partner nations
- United StatesNorwayDenmark
In The Last Decade
Philip Beineke
15 papers receiving 429 citations
Peers
Comparison fields: 5 of 81
- Molecular Biology 120
- Artificial Intelligence 101
- Hepatology 75
- Cardiology and Cardiovascular Medicine 70
- Epidemiology 67
Countries citing papers authored by Philip Beineke
This map shows the geographic impact of Philip Beineke'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 Philip Beineke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip Beineke more than expected).
Fields of papers citing papers by Philip Beineke
This network shows the impact of papers produced by Philip Beineke. 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 Philip Beineke. The network helps show where Philip Beineke may publish in the future.
Co-authorship network of co-authors of Philip Beineke
This figure shows the co-authorship network connecting the top 25 collaborators of Philip Beineke. A scholar is included among the top collaborators of Philip Beineke 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 Philip Beineke. Philip Beineke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 2 | |
| 3 | 25 | |
| 4 | 0 | |
| 5 | 12 | |
| 6 | 11 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 14 | |
| 10 | 65 | |
| 11 | 102 | |
| 12 | 70 | |
| 13 | Mitral annular size predicts Alfieri stitch tension in mitral edge-to-edge repair. | 17 |
| 14 | An exploration of sentiment summarization | 34 |
| 15 | 4 | |
| 16 | 77 |
About Philip Beineke
Philip Beineke is a scholar working on Hepatology, Pathology and Forensic Medicine and Hematology, having authored 16 papers that have together received 456 indexed citations. Recurring topics across this work include Molecular Biology Techniques and Applications (4 papers), Histiocytic Disorders and Treatments (3 papers) and Viral-associated cancers and disorders (3 papers). The work is most often cited by research in Hepatology (75 citations), Artificial Intelligence (101 citations) and Cardiology and Cardiovascular Medicine (70 citations). Philip Beineke has collaborated with scholars based in United States, Norway and Denmark. Frequent co-authors include Gary W. Witherell, Trevor Hastie, Shivakumar Vaithyanathan, Steven Rosenberg, Michael Elashoff, James A. Wingrove, William E. Kraus, Heng Tao, Christopher D. Manning and Karen Fitch. Their work appears in journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.