Matthias Rübner

2.4k total citations
37 papers, 522 citations indexed

About

Matthias Rübner is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Matthias Rübner has authored 37 papers receiving a total of 522 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Oncology, 11 papers in Cancer Research and 7 papers in Molecular Biology. Recurrent topics in Matthias Rübner's work include HER2/EGFR in Cancer Research (5 papers), Cancer Genomics and Diagnostics (5 papers) and Cancer Immunotherapy and Biomarkers (5 papers). Matthias Rübner is often cited by papers focused on HER2/EGFR in Cancer Research (5 papers), Cancer Genomics and Diagnostics (5 papers) and Cancer Immunotherapy and Biomarkers (5 papers). Matthias Rübner collaborates with scholars based in Germany, United States and Switzerland. Matthias Rübner's co-authors include Robert F. Singer, Carolin Körner, Peter A. Fasching, Matthias W. Beckmann, Alexander Hein, Reiner Strick, Lothar Häberle, Arif B. Ekici, Arndt Hartmann and Christina Backes and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Scientific Reports.

In The Last Decade

Matthias Rübner

34 papers receiving 509 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthias Rübner Germany 13 190 164 146 81 72 37 522
Chunjie Xu China 18 238 1.3× 372 2.3× 178 1.2× 87 1.1× 139 1.9× 63 894
Hang Zhang China 17 136 0.7× 205 1.3× 213 1.5× 179 2.2× 144 2.0× 71 819
T. Tanaka Japan 13 93 0.5× 174 1.1× 75 0.5× 79 1.0× 70 1.0× 45 673
Zhenguo Sun China 14 290 1.5× 435 2.7× 99 0.7× 22 0.3× 77 1.1× 33 732
Hidetaka Kinoshita Japan 12 80 0.4× 134 0.8× 56 0.4× 53 0.7× 24 0.3× 53 445
Lihua Zhang China 15 200 1.1× 393 2.4× 63 0.4× 194 2.4× 51 0.7× 41 759
Haowei Wang China 11 163 0.9× 188 1.1× 121 0.8× 34 0.4× 70 1.0× 41 433
Chaojie Liang China 17 266 1.4× 316 1.9× 88 0.6× 209 2.6× 72 1.0× 68 717

Countries citing papers authored by Matthias Rübner

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Rübner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Rübner

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Rübner. A scholar is included among the top collaborators of Matthias Rübner 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 Matthias Rübner. Matthias Rübner 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.
Wilm, Frauke, Matthias Rübner, Corinna Lang‐Schwarz, et al.. (2025). Fully automatic HER2 tissue segmentation for interpretable HER2 scoring. Journal of Pathology Informatics. 17. 100435–100435.
2.
Hanf, Dorothea, Peter A. Fasching, Paul Gaß, et al.. (2024). Impact of CCND1 amplification on the prognosis of hormone receptor–positive, HER2-negative breast cancer patients—correlation of clinical and pathological markers. Breast Cancer Research and Treatment. 210(1). 125–134. 3 indexed citations
3.
Maurer, Jochen, Matthias Rübner, Chao‐Chung Kuo, et al.. (2024). Random forest algorithm identifies miRNA signatures for breast cancer detection and classification from patient urine samples. Therapeutic Advances in Medical Oncology. 16. 12744299–12744299.
4.
Fasching, Peter A., Alexander Hein, Hans‐Christian Kolberg, et al.. (2023). Pembrolizumab in combination with nab-paclitaxel for the treatment of patients with early-stage triple-negative breast cancer – A single-arm phase II trial (NeoImmunoboost, AGO-B-041). European Journal of Cancer. 184. 1–9. 25 indexed citations
5.
6.
Fasching, Peter A., Werner Adler, Matthias Rübner, et al.. (2023). Clinical Characteristics and Prognosis of HER2-0 and HER2-Low-Positive Breast Cancer Patients: Real-World Data from Patients Treated with Neoadjuvant Chemotherapy. Cancers. 15(19). 4678–4678. 3 indexed citations
7.
Müller, Volkmar, Maggie Banys‐Paluchowski, Thomas W. P. Friedl, et al.. (2021). Prognostic relevance of the HER2 status of circulating tumor cells in metastatic breast cancer patients screened for participation in the DETECT study program. ESMO Open. 6(6). 100299–100299. 45 indexed citations
8.
Erber, Ramona, Matthias Rübner, Sven Hauke, et al.. (2020). Impact of fibroblast growth factor receptor 1 (FGFR1) amplification on the prognosis of breast cancer patients. Breast Cancer Research and Treatment. 184(2). 311–324. 12 indexed citations
9.
Kahraman, Mustafa, Thomas Laufer, Tobias Fehlmann, et al.. (2018). MicroRNA in diagnosis and therapy monitoring of early-stage triple-negative breast cancer. Scientific Reports. 8(1). 11584–11584. 108 indexed citations
10.
Erber, Ramona, Arndt Hartmann, Matthias W. Beckmann, et al.. (2018). [TILGen study-immunological targets in patients with breast cancer : Influence of tumor-infiltrating lymphocytes].. PubMed. 39(Suppl 2). 236–240. 1 indexed citations
11.
Schmid, Rafael, Katharina Wolf, Pamela L. Strissel, et al.. (2018). ADSCs and adipocytes are the main producers in the autotaxin–lysophosphatidic acid axis of breast cancer and healthy mammary tissue in vitro. BMC Cancer. 18(1). 1273–1273. 28 indexed citations
12.
Erber, Ramona, Arndt Hartmann, Matthias W. Beckmann, et al.. (2018). TILGen-Studie – Immunologische Angriffspunkte bei Patientinnen mit Brustkrebs. Der Pathologe. 39(S2). 236–240. 1 indexed citations
13.
Bidadi, Behzad, Duan Liu, Krishna R. Kalari, et al.. (2018). Pathway-Based Analysis of Genome-Wide Association Data Identified SNPs in HMMR as Biomarker for Chemotherapy- Induced Neutropenia in Breast Cancer Patients. Frontiers in Pharmacology. 9. 158–158. 19 indexed citations
14.
Burghaus, Stefanie, Peter A. Fasching, Lothar Häberle, et al.. (2017). Genetic risk factors for ovarian cancer and their role for endometriosis risk. Gynecologic Oncology. 145(1). 142–147. 24 indexed citations
15.
Christoph, Jan, Anja‐Katrin Bosserhoff, Elisabeth Naschberger, et al.. (2017). Usability and Suitability of the Omics-Integrating Analysis Platform tranSMART for Translational Research and Education. Applied Clinical Informatics. 8(4). 1173–1183. 5 indexed citations
16.
Wahlbuhl, Mandy, et al.. (2014). Surprising prenatal toxicity of epidermal lipoxygenase-3. Placenta. 35(9). 776–779. 1 indexed citations
17.
Rübner, Matthias, et al.. (2013). Active functionality of piezoceramic modules integrated in aluminum high pressure die castings. Sensors and Actuators A Physical. 207. 84–90. 9 indexed citations
18.
Fasching, PA, Arif B. Ekici, Alexander Hein, et al.. (2013). Breast Cancer Risk – From Genetics to Molecular Understanding of Pathogenesis. Geburtshilfe und Frauenheilkunde. 73(12). 1228–1235. 24 indexed citations
19.
Fasching, PA, Arif B. Ekici, Boris Adamietz, et al.. (2011). Breast Cancer Risk – Genes, Environment and Clinics. Geburtshilfe und Frauenheilkunde. 71(12). 1056–1066. 48 indexed citations
20.
Rübner, Matthias, Carolin Körner, & Robert F. Singer. (2008). Integration of Piezoceramic Modules into Die Castings - Procedure and Functionalities. Advances in science and technology. 56. 170–175. 22 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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