Philip S. Bernard
- Cancer Research top 0.1%
- Breast Cancer Treatment Studies 37
- Cancer Genomics and Diagnostics 17
- Oncology top 0.2%
- HER2/EGFR in Cancer Research 18
- Cancer Cells and Metastasis 7
- Cancer Treatment and Pharmacology 6
- Molecular Biology top 1%
- Molecular Biology Techniques and Applications 22
- Gene expression and cancer classification 19
- Pathology and Forensic Medicine top 0.5%
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- Advanced Breast Cancer Therapies 7
- Co-authors
- Charles M. PerouTorsten O. NielsenJoel S. ParkerMatthew J. EllisMaggie C.U. CheangSamuel LeungSherri R. DaviesDavid Voduc
- Partner nations
- United StatesCanadaSpain
In The Last Decade
Philip S. Bernard
90 papers receiving 11.0k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Cancer Research 5.6k
- Oncology 5.2k
- Molecular Biology 5.0k
- Pathology and Forensic Medicine 1.3k
- Pulmonary and Respiratory Medicine 1.8k
Countries citing papers authored by Philip S. Bernard
This map shows the geographic impact of Philip S. Bernard'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 S. Bernard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip S. Bernard more than expected).
Fields of papers citing papers by Philip S. Bernard
This network shows the impact of papers produced by Philip S. Bernard. 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 S. Bernard. The network helps show where Philip S. Bernard may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Philip S. Bernard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 0 | |
| 2 | 2022 | 22 | |
| 3 | 2019 | 35 | |
| 4 | 2018 | 7 | |
| 5 | 2017 | 14 | |
| 6 | 2017 | 39 | |
| 7 | 2016 | 42 | |
| 8 | 2016 | 19 | |
| 9 | 2014 | 94 | |
| 10 | 2013 | 16 | |
| 11 | 2012 | 220 | |
| 12 | 2012 | 105 | |
| 13 | 2012 | 192 | |
| 14 | 2010 | 194 | |
| 15 | A Comparison of PAM50 Intrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor–Positive Breast Cancerbreakdown → | 2010 | 542 |
| 16 | Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypesbreakdown → | 2009 | 3093 |
| 17 | Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancerbreakdown → | 2009 | 1641 |
| 18 | 2006 | 22 | |
| 19 | 2005 | 49 | |
| 20 | 1999 | 39 |
About Philip S. Bernard
Philip S. Bernard is a scholar working on Cancer Research, Oncology and Pathology and Forensic Medicine, having authored 91 papers that have together received 11.2k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (37 papers), Molecular Biology Techniques and Applications (22 papers), Gene expression and cancer classification (19 papers), HER2/EGFR in Cancer Research (18 papers), Cancer Genomics and Diagnostics (17 papers), Cancer Cells and Metastasis (7 papers), Advanced Breast Cancer Therapies (7 papers) and Cancer Treatment and Pharmacology (6 papers). The work is most often cited by research in Cancer Research (5.6k citations), Oncology (5.2k citations) and Molecular Biology (5.0k citations). Philip S. Bernard has collaborated with scholars based in United States, Canada and Spain. Frequent co-authors include Charles M. Perou, Torsten O. Nielsen, Joel S. Parker, Matthew J. Ellis, Maggie C.U. Cheang, Samuel Leung, Sherri R. Davies, David Voduc, Inge J. Stijleman and Tammi L. Vickery. Their work appears in journals such as Cell, Nature Medicine and Nature Genetics.
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.