Ulrike Peters

49.2k total citations · 1 hit paper
198 papers, 8.0k citations indexed

About

Ulrike Peters is a scholar working on Genetics, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Ulrike Peters has authored 198 papers receiving a total of 8.0k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Genetics, 63 papers in Pathology and Forensic Medicine and 55 papers in Oncology. Recurrent topics in Ulrike Peters's work include Genetic factors in colorectal cancer (40 papers), Colorectal Cancer Screening and Detection (38 papers) and Genetic Associations and Epidemiology (37 papers). Ulrike Peters is often cited by papers focused on Genetic factors in colorectal cancer (40 papers), Colorectal Cancer Screening and Detection (38 papers) and Genetic Associations and Epidemiology (37 papers). Ulrike Peters collaborates with scholars based in United States, Germany and South Africa. Ulrike Peters's co-authors include Nilanjan Chatterjee, Richard B. Hayes, John D. Potter, Stephen J. Chanock, Arthur Schatzkin, Rashmi Sinha, Sholom Wacholder, Emily White, Joel L. Weissfeld and Amy F. Subar and has published in prestigious journals such as The Lancet, JAMA and Nature Communications.

In The Last Decade

Ulrike Peters

189 papers receiving 7.8k citations

Hit Papers

Diet-wide analyses for ri... 2025 2026 2025 5 10 15 20
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.

  1. Diet-wide analyses for risk of colorectal cancer: prospective study of 12,251 incident cases among 542,778 women in the UK
    2025 21 citations Keren Papier, Kathryn E. Bradbury et al. Nature Communications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ulrike Peters United States 52 2.1k 2.0k 1.9k 1.4k 1.2k 198 8.0k
Qi Dai United States 48 1.8k 0.9× 1.4k 0.7× 1.7k 0.9× 2.1k 1.5× 1.4k 1.1× 189 7.6k
Wanqing Wen United States 49 2.4k 1.1× 2.2k 1.1× 1.3k 0.7× 2.1k 1.5× 547 0.4× 179 8.2k
Stephanie J. Weinstein United States 50 2.4k 1.1× 638 0.3× 1.4k 0.7× 1.2k 0.8× 1.0k 0.8× 218 7.1k
Roberd M. Bostick United States 55 1.6k 0.8× 1.3k 0.7× 2.8k 1.5× 2.9k 2.0× 1.6k 1.3× 192 9.6k
Hui Cai United States 53 1.6k 0.8× 795 0.4× 954 0.5× 1.5k 1.0× 985 0.8× 223 7.3k
Peter H. Gann United States 45 2.4k 1.1× 975 0.5× 896 0.5× 2.0k 1.4× 516 0.4× 163 9.3k
Fan Jin China 55 2.4k 1.1× 2.1k 1.1× 1.5k 0.8× 2.6k 1.9× 477 0.4× 225 9.5k
Joseph A. Tangrea United States 41 1.8k 0.9× 890 0.5× 810 0.4× 1.2k 0.9× 989 0.8× 81 5.9k
Ellen Kampman Netherlands 50 2.0k 0.9× 1.1k 0.6× 1.9k 1.0× 3.5k 2.4× 1.1k 0.9× 254 9.5k
Gertraud Maskarinec United States 54 1.1k 0.5× 1.0k 0.5× 1.6k 0.9× 2.8k 1.9× 681 0.5× 263 8.2k

Countries citing papers authored by Ulrike Peters

Since Specialization
Citations

This map shows the geographic impact of Ulrike Peters'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 Ulrike Peters with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ulrike Peters more than expected).

Fields of papers citing papers by Ulrike Peters

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ulrike Peters. 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 Ulrike Peters. The network helps show where Ulrike Peters may publish in the future.

Co-authorship network of co-authors of Ulrike Peters

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

All Works

20 of 20 papers shown
1.
Thomas, Claire E., Yasutoshi Takashima, Daniel D. Buchanan, et al.. (2025). Density of T-cell Subsets in Colorectal Cancer in Relation to Disease-Specific Survival. Cancer Epidemiology Biomarkers & Prevention. 34(7). 1122–1133. 1 indexed citations
2.
Hsu, Li, et al.. (2025). Risk-based screening for early detection of colorectal cancer: an overview. Best Practice & Research Clinical Gastroenterology. 80. 102014–102014.
3.
Papier, Keren, Kathryn E. Bradbury, Angela Balkwill, et al.. (2025). Diet-wide analyses for risk of colorectal cancer: prospective study of 12,251 incident cases among 542,778 women in the UK. Nature Communications. 16(1). 375–375. 21 indexed citations breakdown →
4.
Sun, Quan, Jiawen Chen, Anna V. Mikhaylova, et al.. (2024). Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI. Nature Communications. 15(1). 1016–1016. 17 indexed citations
5.
Rosenthal, Elisabeth A., Li Hsu, Minta Thomas, et al.. (2024). Comparing Ancestry Standardization Approaches for a Transancestry Colorectal Cancer Polygenic Risk Score. Genetic Epidemiology. 49(1). e22590–e22590.
6.
Thomas, Claire E., Yasutoshi Takashima, Evertine Wesselink, et al.. (2024). Association between somatic microsatellite instability, hypermutation status, and specific T cell subsets in colorectal cancer tumors. Frontiers in Immunology. 15. 1505896–1505896. 2 indexed citations
7.
Lai, John, Daniel F. Schmidt, Robert J. MacInnis, et al.. (2023). Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci. Cancer Epidemiology Biomarkers & Prevention. 32(9). 1153–1159.
8.
Lu, Yujia, Yu Zhao, Jenny Chang‐Claude, et al.. (2022). Genetic Predictors for Fecal Propionate and Butyrate-Producing Microbiome Pathway Are Not Associated with Colorectal Cancer Risk: A Mendelian Randomization Analysis. Cancer Epidemiology Biomarkers & Prevention. 32(2). 281–286. 3 indexed citations
9.
Edelmann, Dominic, Federico Canzian, Tabitha A. Harrison, et al.. (2022). Predictive Polygenic Score for Outcome after First-Line Oxaliplatin-Based Chemotherapy in Colorectal Cancer Patients Using Supervised Principal Component Analysis. Cancer Epidemiology Biomarkers & Prevention. 31(11). 2087–2091. 2 indexed citations
10.
Dong, Xinyuan, Yu‐Ru Su, Richard Barfield, et al.. (2020). A general framework for functionally informed set-based analysis: Application to a large-scale colorectal cancer study. PLoS Genetics. 16(8). e1008947–e1008947. 10 indexed citations
11.
Torkko, Kathleen C., Cathee Till, Catherine M. Tangen, et al.. (2020). Vitamin D Pathway and Other Related Polymorphisms and Risk of Prostate Cancer: Results from the Prostate Cancer Prevention Trial. Cancer Prevention Research. 13(6). 521–530. 4 indexed citations
12.
Wang, Xiaoliang, Andrew T. Chan, Martha L. Slattery, et al.. (2018). Influence of Smoking, Body Mass Index, and Other Factors on the Preventive Effect of Nonsteroidal Anti-Inflammatory Drugs on Colorectal Cancer Risk. Cancer Research. 78(16). 4790–4799. 26 indexed citations
13.
Smith, Christopher G., David J. Fisher, Rebecca Harris, et al.. (2015). Analyses of 7,635 Patients with Colorectal Cancer Using Independent Training and Validation Cohorts Show That rs9929218 in CDH1 Is a Prognostic Marker of Survival. Clinical Cancer Research. 21(15). 3453–3461. 16 indexed citations
14.
Kantor, Elizabeth D., Cornelia M. Ulrich, Robert W. Owen, et al.. (2013). Specialty Supplement Use and Biologic Measures of Oxidative Stress and DNA Damage. Cancer Epidemiology Biomarkers & Prevention. 22(12). 2312–2322. 12 indexed citations
15.
Phipps, Amanda I., Polly A. Newcomb, Xabier García‐Albéniz, et al.. (2012). Association Between Colorectal Cancer Susceptibility Loci and Survival Time After Diagnosis With Colorectal Cancer. Gastroenterology. 143(1). 51–54.e4. 28 indexed citations
16.
Takata, Yumie, Alan R. Kristal, Irena B. King, et al.. (2011). Serum Selenium, Genetic Variation in Selenoenzymes, and Risk of Colorectal Cancer: Primary Analysis from the Women's Health Initiative Observational Study and Meta-analysis. Cancer Epidemiology Biomarkers & Prevention. 20(9). 1822–1830. 25 indexed citations
17.
Hutter, Carolyn M., Alicia Young, Heather M. Ochs‐Balcom, et al.. (2011). Replication of Breast Cancer GWAS Susceptibility Loci in the Women's Health Initiative African American SHARe Study. Cancer Epidemiology Biomarkers & Prevention. 20(9). 1950–1959. 48 indexed citations
18.
Trabert, Britton, Anneclaire J. De Roos, Stephen M. Schwartz, et al.. (2010). Non–Dioxin-Like Polychlorinated Biphenyls and Risk of Endometriosis. Environmental Health Perspectives. 118(9). 1280–1285. 52 indexed citations
19.
Dong, Linda M., Cornelia M. Ulrich, Li Hsu, et al.. (2009). Vitamin D Related Genes, CYP24A1 and CYP27B1, and Colon Cancer Risk. Cancer Epidemiology Biomarkers & Prevention. 18(9). 2540–2548. 51 indexed citations
20.
Dong, Linda M., Alan R. Kristal, Ulrike Peters, et al.. (2007). Dietary Supplement Use and Risk of Neoplastic Progression in Esophageal Adenocarcinoma: A Prospective Study. Nutrition and Cancer. 60(1). 39–48. 34 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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