Philip S. Bernard

20.2k total citations · 5 hit papers
91 papers, 11.2k citations indexed

About

Philip S. Bernard is a scholar working on Cancer Research, Molecular Biology and Oncology. According to data from OpenAlex, Philip S. Bernard has authored 91 papers receiving a total of 11.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Cancer Research, 42 papers in Molecular Biology and 39 papers in Oncology. Recurrent topics in Philip S. Bernard's work include Breast Cancer Treatment Studies (37 papers), Molecular Biology Techniques and Applications (22 papers) and Gene expression and cancer classification (19 papers). Philip S. Bernard is often cited by papers focused on Breast Cancer Treatment Studies (37 papers), Molecular Biology Techniques and Applications (22 papers) and Gene expression and cancer classification (19 papers). Philip S. Bernard collaborates with scholars based in United States, Canada and Spain. Philip S. Bernard's 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 and has published in prestigious journals such as Cell, Nature Medicine and Nature Genetics.

In The Last Decade

Philip S. Bernard

90 papers receiving 11.0k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes

2009 3.1k citations Joel S. Parker, Michael E. Mullins et al. Journal of Clinical Oncology profile →
Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer

2009 1.6k citations Maggie C.U. Cheang, Stephen Chia et al. JNCI Journal of the National Cancer Institute profile →
Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes

2011 699 citations Philip S. Bernard, Mark Ebbert et al. profile →
The FET3 gene of S. cerevisiae encodes a multicopper oxidase required for ferrous iron uptake

1994 569 citations Philip S. Bernard et al. profile →
A Comparison of PAM50 Intrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor–Positive Breast Cancer

2010 542 citations Torsten O. Nielsen, Joel S. Parker et al. Clinical Cancer Research profile →

Peers

Philip S. Bernard

ONCOL

PRM

GENET

Joseph Geradts United States

Fernando Schmitt Portugal

Maria Grazia Daidone Italy

Celina G. Kleer United States

Thomas J. Giordano United States

George Somlo United States

Derek C. Radisky United States

David G. Beer United States

Juan Palazzo United States

Göran Landberg Sweden

Joseph Geradts United States

Philip S. Bernard

5.1k ×0.9

6.5k ×1.3

ONCOL

5.1k ×1.0

2.1k ×1.2

PRM

1.9k ×1.4

GENET

Citations per year, relative to Philip S. Bernard Philip S. Bernard (= 1×) peers Joseph Geradts

Countries citing papers authored by Philip S. Bernard

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Philip S. Bernard

This figure shows the co-authorship network connecting the top 25 collaborators of Philip S. Bernard. A scholar is included among the top collaborators of Philip S. Bernard 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 S. Bernard. Philip S. Bernard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Oyler, Douglas R., et al.. (2022). Factors influencing opioid prescribing after tooth extraction. The Journal of the American Dental Association. 153(9). 868–877.

Butterfield, Andrew, Sandra D. Scherer, Emilio Cortes-Sanchez, et al.. (2022). Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer. Communications Biology. 5(1). 794–794. 22 indexed citations

Stewart, Rachel L., Rachel E. Factor, N. Lynn Henry, et al.. (2019). A Multigene Assay Determines Risk of Recurrence in Patients with Triple-Negative Breast Cancer. Cancer Research. 79(13). 3466–3478. 35 indexed citations

Knight, Stacey, Carol Sweeney, Rachel E. Factor, et al.. (2018). Reparameterization of PAM50 Expression Identifies Novel Breast Tumor Dimensions and Leads to Discovery of a Genome-Wide Significant Breast Cancer Locus at 12q15. Cancer Epidemiology Biomarkers & Prevention. 27(6). 644–652. 7 indexed citations

Delker, Don A., N. Jewel Samadder, Wade S. Samowitz, et al.. (2017). Chemoprevention with Cyclooxygenase and Epidermal Growth Factor Receptor Inhibitors in Familial Adenomatous Polyposis Patients: mRNA Signatures of Duodenal Neoplasia. Cancer Prevention Research. 11(1). 4–15. 14 indexed citations

Feliciano, Elizabeth M. Cespedes, Marilyn L. Kwan, Lawrence H. Kushi, et al.. (2017). Body mass index, PAM50 subtype, recurrence, and survival among patients with nonmetastatic breast cancer. Cancer. 123(13). 2535–2542. 39 indexed citations

Jones, Lee W., Marilyn L. Kwan, Erin Weltzien, et al.. (2016). Exercise and Prognosis on the Basis of Clinicopathologic and Molecular Features in Early-Stage Breast Cancer: The LACE and Pathways Studies. Cancer Research. 76(18). 5415–5422. 42 indexed citations

Bradford, James, Angela Cox, Philip S. Bernard, & Nicola J. Camp. (2016). Consensus Analysis of Whole Transcriptome Profiles from Two Breast Cancer Patient Cohorts Reveals Long Non-Coding RNAs Associated with Intrinsic Subtype and the Tumour Microenvironment. PLoS ONE. 11(9). e0163238–e0163238. 19 indexed citations

Sweeney, Carol, Philip S. Bernard, Rachel E. Factor, et al.. (2014). Intrinsic Subtypes from PAM50 Gene Expression Assay in a Population-Based Breast Cancer Cohort: Differences by Age, Race, and Tumor Characteristics. Cancer Epidemiology Biomarkers & Prevention. 23(5). 714–724. 94 indexed citations

10.

Wilkerson, Matthew D., D. Neil Hayes, Patrick J. Roberts, et al.. (2013). Prediction of Lung Cancer Histological Types by RT-qPCR Gene Expression in FFPE Specimens. Journal of Molecular Diagnostics. 15(4). 485–497. 16 indexed citations

11.

Chia, Stephen, Vivien Bramwell, Dongsheng Tu, et al.. (2012). A 50-Gene Intrinsic Subtype Classifier for Prognosis and Prediction of Benefit from Adjuvant Tamoxifen. Clinical Cancer Research. 18(16). 4465–4472. 220 indexed citations

12.

Cheang, Maggie C.U., K. David Voduc, Dongsheng Tu, et al.. (2012). Responsiveness of Intrinsic Subtypes to Adjuvant Anthracycline Substitution in the NCIC.CTG MA.5 Randomized Trial. Clinical Cancer Research. 18(8). 2402–2412. 105 indexed citations

13.

Wilkerson, Matthew D., Xiaoying Yin, Vonn Walter, et al.. (2012). Differential Pathogenesis of Lung Adenocarcinoma Subtypes Involving Sequence Mutations, Copy Number, Chromosomal Instability, and Methylation. PLoS ONE. 7(5). e36530–e36530. 192 indexed citations

14.

Wilkerson, Matthew D., Xiaoying Yin, Katherine A. Hoadley, et al.. (2010). Lung Squamous Cell Carcinoma mRNA Expression Subtypes Are Reproducible, Clinically Important, and Correspond to Normal Cell Types. Clinical Cancer Research. 16(19). 4864–4875. 194 indexed citations

15.

Nielsen, Torsten O., Joel S. Parker, Samuel Leung, et al.. (2010). A Comparison of PAM50 Intrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor–Positive Breast Cancer. Clinical Cancer Research. 16(21). 5222–5232. 542 indexed citations breakdown →

16.

Parker, Joel S., Michael E. Mullins, Maggie C.U. Cheang, et al.. (2009). Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes. Journal of Clinical Oncology. 27(8). 1160–1167. 3093 indexed citations breakdown →

17.

Cheang, Maggie C.U., Stephen Chia, David Voduc, et al.. (2009). Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer. JNCI Journal of the National Cancer Institute. 101(10). 736–750. 1641 indexed citations breakdown →

18.

Ciocca, Vincenzo, Alessandro Bombonati, Zoran Gatalica, et al.. (2006). Cytokeratin profiles of male breast cancers. Histopathology. 49(4). 365–370. 22 indexed citations

19.

Lewis, Tracey, John Elder Robison, Roy R. L. Bastien, et al.. (2005). Molecular classification of melanoma using real‐time quantitative reverse transcriptase‐polymerase chain reaction. Cancer. 104(8). 1678–1686. 49 indexed citations

20.

Gundry, Cameron N., et al.. (1999). Rapid F508del and F508C Assay Using Fluorescent Hybridization Probes. Genetic Testing. 3(4). 365–370. 39 indexed citations

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.

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