Elisabeth Heßmann

3.2k total citations
39 papers, 1.3k citations indexed

About

Elisabeth Heßmann is a scholar working on Oncology, Molecular Biology and Cancer Research. According to data from OpenAlex, Elisabeth Heßmann has authored 39 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Oncology, 25 papers in Molecular Biology and 8 papers in Cancer Research. Recurrent topics in Elisabeth Heßmann's work include Pancreatic and Hepatic Oncology Research (24 papers), Epigenetics and DNA Methylation (9 papers) and Cancer Cells and Metastasis (6 papers). Elisabeth Heßmann is often cited by papers focused on Pancreatic and Hepatic Oncology Research (24 papers), Epigenetics and DNA Methylation (9 papers) and Cancer Cells and Metastasis (6 papers). Elisabeth Heßmann collaborates with scholars based in Germany, United States and United Kingdom. Elisabeth Heßmann's co-authors include Volker Ellenrieder, Jens T. Siveke, Albrecht Neeße, Steven A. Johnsen, Shiv K. Singh, Thomas M. Gress, S Buchholz, İhsan Ekin Demir, Günter Schneider and Jochen Gaedcke and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Physiological Reviews.

In The Last Decade

Elisabeth Heßmann

36 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Elisabeth Heßmann Germany 17 773 750 305 203 153 39 1.3k
Evangeline Mose United States 18 563 0.7× 551 0.7× 239 0.8× 283 1.4× 154 1.0× 25 1.2k
Rama Krishna Nimmakayala United States 18 740 1.0× 547 0.7× 341 1.1× 247 1.2× 99 0.6× 28 1.2k
Yan‐Miao Huo China 21 559 0.7× 534 0.7× 435 1.4× 276 1.4× 150 1.0× 54 1.2k
Meredith A. Collins United States 12 750 1.0× 1.0k 1.4× 371 1.2× 316 1.6× 284 1.9× 16 1.5k
Kenji Tsuchihashi Japan 18 655 0.8× 625 0.8× 314 1.0× 190 0.9× 200 1.3× 69 1.4k
Chi Tat Lam Hong Kong 10 889 1.2× 940 1.3× 549 1.8× 196 1.0× 138 0.9× 12 1.6k
Mónica Musteanu Spain 14 415 0.5× 552 0.7× 181 0.6× 121 0.6× 107 0.7× 32 972
Mikinori Sato Japan 19 603 0.8× 704 0.9× 302 1.0× 214 1.1× 239 1.6× 59 1.4k
Jérémy Bastid France 15 697 0.9× 888 1.2× 295 1.0× 480 2.4× 76 0.5× 22 1.6k
Dingkong Liang China 18 634 0.8× 573 0.8× 439 1.4× 96 0.5× 140 0.9× 21 1.1k

Countries citing papers authored by Elisabeth Heßmann

Since Specialization
Citations

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

Fields of papers citing papers by Elisabeth Heßmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elisabeth Heßmann

This figure shows the co-authorship network connecting the top 25 collaborators of Elisabeth Heßmann. A scholar is included among the top collaborators of Elisabeth Heßmann 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 Elisabeth Heßmann. Elisabeth Heßmann 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.
Küffer, Stefan, Lukas Klein, Christof Lenz, et al.. (2025). TP53 missense–specific transcriptional plasticity drives resistance against cell cycle inhibitors in pancreatic cancer. Science Advances. 11(27). eadu2339–eadu2339.
2.
Sitte, Maren, Philipp Ströbel, Volker Ellenrieder, et al.. (2024). A single-cell strategy for the identification of intronic variants related to mis-splicing in pancreatic cancer. NAR Genomics and Bioinformatics. 6(2). lqae057–lqae057. 2 indexed citations
3.
4.
Zhang, Zhe, Xin Wang, Feda H. Hamdan, et al.. (2023). NFATc1 Is a Central Mediator of EGFR-Induced ARID1A Chromatin Dissociation During Acinar Cell Reprogramming. Cellular and Molecular Gastroenterology and Hepatology. 15(5). 1219–1246. 3 indexed citations
5.
Rahman, Raza‐Ur, Christine S. Gibhardt, K Reutlinger, et al.. (2022). NFATc1 signaling drives chronic ER stress responses to promote NAFLD progression. Gut. 71(12). 2561–2573. 46 indexed citations
6.
Klein, Lukas, Florian Wegwitz, Elisa Espinet, et al.. (2022). Axon guidance receptor ROBO3 modulates subtype identity and prognosis via AXL-associated inflammatory network in pancreatic cancer. JCI Insight. 7(16). 5 indexed citations
7.
Zhang, Zhe, Silke Kaulfuß, Bernd Wollnik, et al.. (2022). TP53-Status-Dependent Oncogenic EZH2 Activity in Pancreatic Cancer. Cancers. 14(14). 3451–3451. 10 indexed citations
8.
Schneeweis, Christian, Zonera Hassan, Chiara Falcomatà, et al.. (2022). AP1/Fra1 confers resistance to MAPK cascade inhibition in pancreatic cancer. Cellular and Molecular Life Sciences. 80(1). 12–12. 6 indexed citations
9.
Thomale, Jürgen, et al.. (2021). HSP90 Inhibition Synergizes with Cisplatin to Eliminate Basal-like Pancreatic Ductal Adenocarcinoma Cells. Cancers. 13(24). 6163–6163. 14 indexed citations
10.
Kutschat, Ana P., Feda H. Hamdan, Xin Wang, et al.. (2021). STIM1 Mediates Calcium-Dependent Epigenetic Reprogramming in Pancreatic Cancer. Cancer Research. 81(11). 2943–2955. 11 indexed citations
11.
Reutlinger, K, Jochen Gaedcke, Philipp Ströbel, et al.. (2021). Chromatin-Independent Interplay of NFATc1 and EZH2 in Pancreatic Cancer. Cells. 10(12). 3463–3463. 4 indexed citations
12.
Heßmann, Elisabeth, et al.. (2021). Epigenetic Therapeutic Strategies to Target Molecular and Cellular Heterogeneity in Pancreatic Cancer. Visceral Medicine. 38(1). 11–19. 9 indexed citations
13.
Kari, Vijayalakshmi, Feda H. Hamdan, Jochen Gaedcke, et al.. (2019). Cytosolic 5′-nucleotidase 1A is overexpressed in pancreatic cancer and mediates gemcitabine resistance by reducing intracellular gemcitabine metabolites. EBioMedicine. 40. 394–405. 24 indexed citations
14.
Bremer, Sebastian, Lena‐Christin Conradi, Ahmad Amanzada, et al.. (2019). Enhancer of Zeste Homolog 2 in Colorectal Cancer Development and Progression. Digestion. 102(2). 227–235. 19 indexed citations
15.
Buchholz, S, et al.. (2018). Utilizing High Resolution Ultrasound to Monitor Tumor Onset and Growth in Genetically Engineered Pancreatic Cancer Models. Journal of Visualized Experiments. 15 indexed citations
16.
Emons, Georg, Melanie Spitzner, Noam Auslander, et al.. (2017). Chemoradiotherapy Resistance in Colorectal Cancer Cells is Mediated by Wnt/β-catenin Signaling. Molecular Cancer Research. 15(11). 1481–1490. 104 indexed citations
17.
Mishra, Vivek Kumar, Florian Wegwitz, Robyn Laura Kosinsky, et al.. (2017). Histone deacetylase class-I inhibition promotes epithelial gene expression in pancreatic cancer cells in a BRD4- and MYC-dependent manner. Nucleic Acids Research. 45(11). 6334–6349. 65 indexed citations
18.
Heßmann, Elisabeth, Lukas Klein, Vijayalakshmi Kari, et al.. (2017). Fibroblast drug scavenging increases intratumoural gemcitabine accumulation in murine pancreas cancer. Gut. 67(3). 497–507. 148 indexed citations
19.
Baumgart, Sandra, Jin‐San Zhang, Daniel D. Billadeau, et al.. (2016). GSK-3β Governs Inflammation-Induced NFATc2 Signaling Hubs to Promote Pancreatic Cancer Progression. Molecular Cancer Therapeutics. 15(3). 491–502. 37 indexed citations
20.
Heßmann, Elisabeth, Steven A. Johnsen, Jens T. Siveke, & Volker Ellenrieder. (2016). Epigenetic treatment of pancreatic cancer: is there a therapeutic perspective on the horizon?. Gut. 66(1). 168–179. 94 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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