Jürgen Geisler

8.6k total citations · 1 hit paper
146 papers, 5.1k citations indexed

About

Jürgen Geisler is a scholar working on Genetics, Oncology and Cancer Research. According to data from OpenAlex, Jürgen Geisler has authored 146 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Genetics, 68 papers in Oncology and 52 papers in Cancer Research. Recurrent topics in Jürgen Geisler's work include Estrogen and related hormone effects (67 papers), Breast Cancer Treatment Studies (38 papers) and HER2/EGFR in Cancer Research (19 papers). Jürgen Geisler is often cited by papers focused on Estrogen and related hormone effects (67 papers), Breast Cancer Treatment Studies (38 papers) and HER2/EGFR in Cancer Research (19 papers). Jürgen Geisler collaborates with scholars based in Norway, Sweden and United Kingdom. Jürgen Geisler's co-authors include Per Eystein Lønning, Mitch Dowsett, Gun Anker, Ben P. Haynes, Dagfinn Ekse, Nicholas King, Lars Ottestad, Anne Hansen Ree, Torbjørn Omland and Geeta Gulati and has published in prestigious journals such as Nucleic Acids Research, Circulation and Nature Communications.

In The Last Decade

Jürgen Geisler

140 papers receiving 5.0k citations

Hit Papers

Prevention of cardiac dysfunction during adjuvant breast ... 2016 2026 2019 2022 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jürgen Geisler Norway 36 2.5k 2.5k 1.4k 1.3k 779 146 5.1k
Fiorella Guadagni Italy 42 2.0k 0.8× 394 0.2× 757 0.5× 1.6k 1.2× 759 1.0× 210 5.7k
Johan Hartman Sweden 34 2.4k 1.0× 1.9k 0.8× 1.9k 1.3× 2.7k 2.0× 733 0.9× 113 6.7k
Yasuo Miyoshi Japan 52 3.4k 1.4× 1.6k 0.7× 2.3k 1.6× 4.6k 3.4× 1.0k 1.3× 252 9.3k
Peter Olson United States 31 3.3k 1.4× 307 0.1× 1.9k 1.3× 4.4k 3.3× 829 1.1× 86 8.3k
Ja Seung Koo South Korea 43 2.4k 1.0× 509 0.2× 2.8k 2.0× 2.7k 2.0× 807 1.0× 231 6.3k
Ellen L. Goode United States 40 1.7k 0.7× 1.4k 0.6× 1.6k 1.1× 3.1k 2.3× 803 1.0× 148 6.0k
Sabine C. Linn Netherlands 48 4.7k 1.9× 1.5k 0.6× 3.4k 2.4× 3.2k 2.4× 2.4k 3.0× 231 9.1k
Filio Billia Canada 35 626 0.3× 510 0.2× 742 0.5× 2.4k 1.8× 227 0.3× 158 5.2k
Seiichi Takenoshita Japan 41 2.0k 0.8× 386 0.2× 1.2k 0.8× 3.3k 2.4× 781 1.0× 299 6.1k
B. Mark Woerner United States 20 1.1k 0.4× 1.5k 0.6× 711 0.5× 1.3k 0.9× 365 0.5× 21 4.8k

Countries citing papers authored by Jürgen Geisler

Since Specialization
Citations

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

Fields of papers citing papers by Jürgen Geisler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jürgen Geisler

This figure shows the co-authorship network connecting the top 25 collaborators of Jürgen Geisler. A scholar is included among the top collaborators of Jürgen Geisler 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 Jürgen Geisler. Jürgen Geisler 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.
Hoff, Solveig Roth, et al.. (2025). Comparative analysis of deep learning architectures for breast region segmentation with a novel breast boundary proposal. Scientific Reports. 15(1). 8806–8806. 3 indexed citations
2.
Kastora, Stavroula, Eirini Pantiora, Hatem A. Azim, et al.. (2025). Safety of topical estrogen therapy during adjuvant endocrine treatment among patients with breast cancer: A meta-analysis based expert panel discussion. Cancer Treatment Reviews. 133. 102880–102880. 3 indexed citations
3.
Farkas, Lóránt, Daehoon Park, Yan Liu, et al.. (2025). High Ki67 expression, HER2 overexpression, and low progesterone receptor levels in high-grade DCIS: significant associations with clinical practice implications. Frontiers in Oncology. 15. 1467664–1467664. 1 indexed citations
4.
Schmiester, Leonard, Fara Brasó‐Maristany, Blanca González‐Farré, et al.. (2024). Computational Model Predicts Patient Outcomes in Luminal B Breast Cancer Treated with Endocrine Therapy and CDK4/6 Inhibition. Clinical Cancer Research. 30(17). 3779–3787. 1 indexed citations
5.
Park, Daehoon, et al.. (2023). Subtypes of high-grade breast ductal carcinoma in situ (DCIS): incidence and potential clinical impact. Breast Cancer Research and Treatment. 201(2). 329–338. 5 indexed citations
7.
Deng, Wei, Jürgen Geisler, Stephanie Geisler, et al.. (2022). Clonal evolution in primary breast cancers under sequential epirubicin and docetaxel monotherapy. Genome Medicine. 14(1). 86–86. 10 indexed citations
10.
Sauer, Torill, Vahid Bemanian, Jonas Christoffer Lindstrøm, et al.. (2019). The NEOLETEXE Trial: A Neoadjuvant Cross-Over Study Exploring the Lack of Cross Resistance Between Aromatase Inhibitors. Future Oncology. 15(32). 3675–3682. 8 indexed citations
11.
12.
Larionov, Alexey A., Jürgen Geisler, Stian Knappskog, et al.. (2016). Treatment with aromatase inhibitors stimulates the expression of epidermal growth factor receptor-1 and neuregulin 1 in ER positive/HER-2/neu non-amplified primary breast cancers. The Journal of Steroid Biochemistry and Molecular Biology. 165(Pt B). 228–235. 5 indexed citations
13.
Bemanian, Vahid, et al.. (2015). The Epidermal Growth Factor Receptor (EGFR / HER-1) Gatekeeper Mutation T790M Is Present in European Patients with Early Breast Cancer. PLoS ONE. 10(8). e0134398–e0134398. 16 indexed citations
14.
Harbst, Katja, Johan Staaf, Martin Lauss, et al.. (2012). Molecular Profiling Reveals Low- and High-Grade Forms of Primary Melanoma. Clinical Cancer Research. 18(15). 4026–4036. 72 indexed citations
15.
Jönsson, Göran, Christian Busch, Stian Knappskog, et al.. (2010). Gene Expression Profiling–Based Identification of Molecular Subtypes in Stage IV Melanomas with Different Clinical Outcome. Clinical Cancer Research. 16(13). 3356–3367. 189 indexed citations
16.
Haynes, Ben P., Anne Hege Straume, Jürgen Geisler, et al.. (2010). Intratumoral Estrogen Disposition in Breast Cancer. Clinical Cancer Research. 16(6). 1790–1801. 75 indexed citations
17.
Dixon, J. Michael, Jürgen Geisler, Ernst A. Lien, et al.. (2009). Nuclear receptor co-activators and HER-2/neu are upregulated in breast cancer patients during neo-adjuvant treatment with aromatase inhibitors. British Journal of Cancer. 101(8). 1253–1260. 32 indexed citations
18.
Geisler, Jürgen, Dagfinn Ekse, & Per Eystein Lønning. (2006). The aromatase inactivator exemestane (Aromasin®) decreases plasma leptin levels in postmenopausal breast cancer patients. Cancer Research. 66. 98–98. 4 indexed citations
19.
Knappskog, Stian, Jürgen Geisler, Thomas Arnesen, Johan R. Lillehaug, & Per Eystein Lønning. (2006). A novel type of deletion in the CDKN2A gene identified in a melanoma‐prone family. Genes Chromosomes and Cancer. 45(12). 1155–1163. 15 indexed citations
20.
Lønning, Per Eystein, Björn Erikstein, Anne Irene Hagen, et al.. (2001). The potential for aromatase inhibition in breast cancer prevention.. PubMed. 7(12 Suppl). 4423s–4412s. 6 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026