Diana Behrens

808 total citations
27 papers, 621 citations indexed

About

Diana Behrens is a scholar working on Oncology, Molecular Biology and Cancer Research. According to data from OpenAlex, Diana Behrens has authored 27 papers receiving a total of 621 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 15 papers in Molecular Biology and 4 papers in Cancer Research. Recurrent topics in Diana Behrens's work include Pancreatic and Hepatic Oncology Research (11 papers), Cancer Cells and Metastasis (8 papers) and 3D Printing in Biomedical Research (4 papers). Diana Behrens is often cited by papers focused on Pancreatic and Hepatic Oncology Research (11 papers), Cancer Cells and Metastasis (8 papers) and 3D Printing in Biomedical Research (4 papers). Diana Behrens collaborates with scholars based in Germany, United Kingdom and Italy. Diana Behrens's co-authors include Iduna Fichtner, Wolfgang Walther, Jason H. Gill, Katrin Wenzel, Renate Stahn, Aldo Scarpa, Christopher Heeschen, Hans Lehrach, Wasco Wruck and Rita T. Lawlor and has published in prestigious journals such as Nature Communications, PLoS ONE and Cancer Research.

In The Last Decade

Diana Behrens

27 papers receiving 615 citations

Peers

Diana Behrens

ONCOL

IMMUN

A. Yu. Baryshnikov Russia

Stephen I. Rudnick United States

André‐René Blaudszun Germany

Akifumi Mizutani Japan

Heidi A. Neubauer Austria

Larissa Lezina United Kingdom

Barbara J. Bailey United States

Guo‐Kai Feng China

Christopher M. Fife Australia

Jonathan Rios‐Doria United States

A. Yu. Baryshnikov Russia

Diana Behrens

445 ×1.3

186 ×0.7

ONCOL

69 ×0.7

133 ×1.4

90 ×1.0

IMMUN

Citations per year, relative to Diana Behrens Diana Behrens (= 1×) peers A. Yu. Baryshnikov

Countries citing papers authored by Diana Behrens

Since Specialization

Citations

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

Fields of papers citing papers by Diana Behrens

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diana Behrens

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

All Works

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20 of 20 papers shown

Förster, Jan, Sven‐Thorsten Liffers, Christopher Schröder, et al.. (2024). Pancreatic cancer acquires resistance to MAPK pathway inhibition by clonal expansion and adaptive DNA hypermethylation. Clinical Epigenetics. 16(1). 13–13. 5 indexed citations

Zheng, Quan, Jiajia Tang, Alexandra Aicher, et al.. (2023). Inhibiting NR5A2 targets stemness in pancreatic cancer by disrupting SOX2/MYC signaling and restoring chemosensitivity. Journal of Experimental & Clinical Cancer Research. 42(1). 323–323. 7 indexed citations

Behrens, Diana, Theresia Conrad, Michael W. Becker, et al.. (2023). Establishment and Thorough Characterization of Xenograft (PDX) Models Derived from Patients with Pancreatic Cancer for Molecular Analyses and Chemosensitivity Testing. Cancers. 15(24). 5753–5753. 3 indexed citations

Zepp, Michael, Ergül Eyol, Mathias Dahlmann, et al.. (2023). EPI-X4, a CXCR4 antagonist inhibits tumor growth in pancreatic cancer and lymphoma models. Peptides. 175. 171111–171111. 4 indexed citations

Kobelt, Dennis, Jutta Aumann, Diana Behrens, et al.. (2021). Effective Oncoleaking Treatment of Pancreatic Cancer by Claudin-Targeted Suicide Gene Therapy with Clostridium perfringens Enterotoxin (CPE). Cancers. 13(17). 4393–4393. 18 indexed citations

Trabulo, Sara Maria David, Estelle Collin, Ying Liu, et al.. (2021). Bioengineered 3D models of human pancreatic cancer recapitulate in vivo tumour biology. Nature Communications. 12(1). 5623–5623. 97 indexed citations

Heuberger, Julian, Ramón Vidal, Antonio Berenguer, et al.. (2020). The epigenetic regulator Mll1 is required for Wnt-driven intestinal tumorigenesis and cancer stemness. Nature Communications. 11(1). 6422–6422. 44 indexed citations

Zhao, Ben, Jiangning Gu, Marija Trajkovic‐Arsic, et al.. (2020). TFEB-mediated lysosomal biogenesis and lysosomal drug sequestration confer resistance to MEK inhibition in pancreatic cancer. Cell Death Discovery. 6(1). 33 indexed citations

Heitzer, Ellen, Arwin Groenewoud, Birgit Lohberger, et al.. (2019). Human melanoma brain metastases cell line MUG-Mel1, isolated clones and their detailed characterization. Scientific Reports. 9(1). 4096–4096. 7 indexed citations

10.

Behrens, Diana, Christopher Heeschen, Malte Buchholz, et al.. (2018). Abstract 4093: Preclinical evaluation of novel treatment strategies in patient-derived xenograft (PDX) models of pancreatic cancer. Cancer Research. 78(13_Supplement). 4093–4093. 1 indexed citations

11.

Behrens, Diana, Wolfgang Walther, & Iduna Fichtner. (2017). Pancreatic cancer models for translational research. Pharmacology & Therapeutics. 173. 146–158. 26 indexed citations

12.

Zhou, Yan, S. E. Lysenko, Linara Gabitova, et al.. (2016). Screening of Conditionally Reprogrammed Patient-Derived Carcinoma Cells Identifies ERCC3–MYC Interactions as a Target in Pancreatic Cancer. Clinical Cancer Research. 22(24). 6153–6163. 47 indexed citations

13.

Sannino, Giuseppina, Nicole Armbruster, Diana Behrens, et al.. (2016). Role of BCL9L in transforming growth factor-β (TGF-β)-induced epithelial-to-mesenchymal-transition (EMT) and metastasis of pancreatic cancer. Oncotarget. 7(45). 73725–73738. 24 indexed citations

14.

Kobelt, Dennis, Jutta Aumann, Manuel Schmidt, et al.. (2014). Preclinical study on combined chemo‐ and nonviral gene therapy for sensitization of melanoma using a human TNF‐alpha expressing MIDGE DNA vector. Molecular Oncology. 8(3). 609–619. 11 indexed citations

15.

Redmer, Torben, Yvonne Welte, Diana Behrens, et al.. (2014). The Nerve Growth Factor Receptor CD271 Is Crucial to Maintain Tumorigenicity and Stem-Like Properties of Melanoma Cells. PLoS ONE. 9(5). e92596–e92596. 77 indexed citations

16.

Behrens, Diana, et al.. (2014). 624: In vivo models of pancreatic cancer for translational medicine. European Journal of Cancer. 50. S148–S149. 2 indexed citations

17.

Fichtner, Iduna, Diana Behrens, James Claffey, et al.. (2011). The Antiangiogenic and Antitumoral Activity of Titanocene Y* In Vivo. Letters in Drug Design & Discovery. 8(4). 302–307. 15 indexed citations

18.

Behrens, Diana, Jason H. Gill, & Iduna Fichtner. (2007). Loss of tumourigenicity of stably ERβ-transfected MCF-7 breast cancer cells. Molecular and Cellular Endocrinology. 274(1-2). 19–29. 34 indexed citations

19.

Behrens, Diana, et al.. (2004). Liposomal 4-hydroxy-tamoxifen: effect on cellular uptake and resulting cytotoxicity in drug resistant breast cancer cells in vitro. Breast Cancer Research and Treatment. 87(3). 245–254. 11 indexed citations

20.

Stahn, Renate, et al.. (2003). Effect of sialyl Lewis X-glycoliposomes on the inhibition of E-selectin-mediated tumour cell adhesion in vitro. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1660(1-2). 31–40. 45 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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