Daniel Eberhard

1.5k total citations
37 papers, 1.1k citations indexed

About

Daniel Eberhard is a scholar working on Surgery, Molecular Biology and Genetics. According to data from OpenAlex, Daniel Eberhard has authored 37 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Surgery, 16 papers in Molecular Biology and 12 papers in Genetics. Recurrent topics in Daniel Eberhard's work include Pancreatic function and diabetes (22 papers), Diabetes and associated disorders (8 papers) and Genetics and Neurodevelopmental Disorders (5 papers). Daniel Eberhard is often cited by papers focused on Pancreatic function and diabetes (22 papers), Diabetes and associated disorders (8 papers) and Genetics and Neurodevelopmental Disorders (5 papers). Daniel Eberhard collaborates with scholars based in Germany, United Kingdom and United States. Daniel Eberhard's co-authors include Eckhard Lammert, David Tosh, Harald Jockusch, Martin Kragl, Làszlò Tora, I. Grummt, Jonathan Slack, Udo Rudloff, Saeed Katiraei and Ko Willems van Dijk and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Daniel Eberhard

37 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Eberhard Germany 19 541 401 215 160 122 37 1.1k
Per Antonson Sweden 22 783 1.4× 181 0.5× 424 2.0× 126 0.8× 158 1.3× 39 1.5k
John Le Lay United States 19 790 1.5× 579 1.4× 300 1.4× 261 1.6× 182 1.5× 22 1.5k
Siew Tein Wang Singapore 10 880 1.6× 346 0.9× 110 0.5× 127 0.8× 214 1.8× 12 1.2k
Esw Ngan Hong Kong 27 868 1.6× 592 1.5× 401 1.9× 201 1.3× 40 0.3× 62 1.9k
Essam M. Abdelalim Qatar 22 619 1.1× 504 1.3× 250 1.2× 178 1.1× 90 0.7× 75 1.2k
Dong‐Sik Ham South Korea 14 329 0.6× 276 0.7× 149 0.7× 153 1.0× 90 0.7× 24 763
Mohammad Mahdi Motazacker Netherlands 14 549 1.0× 437 1.1× 225 1.0× 261 1.6× 60 0.5× 18 1.2k
Gregoire Biollaz Switzerland 7 216 0.4× 312 0.8× 263 1.2× 161 1.0× 141 1.2× 7 912
Heike Naumann Germany 15 800 1.5× 164 0.4× 104 0.5× 45 0.3× 135 1.1× 18 1.3k
Maria E. Wilson United States 15 552 1.0× 624 1.6× 472 2.2× 275 1.7× 98 0.8× 25 1.2k

Countries citing papers authored by Daniel Eberhard

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Eberhard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Eberhard

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Eberhard. A scholar is included among the top collaborators of Daniel Eberhard 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 Daniel Eberhard. Daniel Eberhard 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.
Eberhard, Daniel, Philipp Niklas Ostermann, Philip Kirschner, et al.. (2024). Semaphorin-3A regulates liver sinusoidal endothelial cell porosity and promotes hepatic steatosis. Nature Cardiovascular Research. 3(6). 734–753. 8 indexed citations
2.
Behnke, Kristina, Philip Kirschner, Sonja Hartwig, et al.. (2024). Identification of myeloid-derived growth factor as a mechanically-induced, growth-promoting angiocrine signal for human hepatocytes. Nature Communications. 15(1). 1076–1076. 7 indexed citations
3.
Belgardt, Bengt‐Frederik, Daniel Eberhard, Ertan Mayatepek, et al.. (2024). The N-Methyl-D-Aspartate Receptor Antagonist Dextromethorphan Improves Glucose Homeostasis and Preserves Pancreatic Islets in NOD Mice. Hormone and Metabolic Research. 56(3). 223–234. 4 indexed citations
4.
Kirschner, Philip, Natalia I. Krupenko, Philipp Westhoff, et al.. (2023). Pancreatic islet protection at the expense of secretory function involves serine-linked mitochondrial one-carbon metabolism. Cell Reports. 42(6). 112615–112615. 6 indexed citations
5.
Maier, Tanja, et al.. (2021). Exploring the transmucosal permeability of cyclobenzaprine: A comparative preformulation by standardized and controlled ex vivo and in vitro permeation studies. International Journal of Pharmaceutics. 601. 120574–120574. 4 indexed citations
6.
Schuler, Dominik, Dimitrios Dimitroulis, Roberto Sansone, et al.. (2019). Requirement of β1 integrin for endothelium-dependent vasodilation and collateral formation in hindlimb ischemia. Scientific Reports. 9(1). 16931–16931. 11 indexed citations
7.
8.
Lorenz, Linda F., Jennifer Axnick, Shentong Fang, et al.. (2018). Mechanosensing by β1 integrin induces angiocrine signals for liver growth and survival. Nature. 562(7725). 128–132. 120 indexed citations
9.
Jain, Deepak, Daniel Eberhard, Jan Eglinger, et al.. (2015). DJ-1 Protects Pancreatic Beta Cells from Cytokine- and Streptozotocin-Mediated Cell Death. PLoS ONE. 10(9). e0138535–e0138535. 20 indexed citations
10.
O’Neill, Kathy E., Shifaan Thowfeequ, Wan‐Chun Li, et al.. (2014). Hepatocyte-Ductal Transdifferentiation Is Mediated by Reciprocal Repression of SOX9 and C/EBPα. Cellular Reprogramming. 16(5). 314–323. 12 indexed citations
11.
Fischer, Julia, et al.. (2014). FTO Is a Relevant Factor for the Development of the Metabolic Syndrome in Mice. PLoS ONE. 9(8). e105349–e105349. 15 indexed citations
12.
Jain, Deepak, Ruchi Jain, Daniel Eberhard, et al.. (2012). Age- and diet-dependent requirement of DJ-1 for glucose homeostasis in mice with implications for human type 2 diabetes. Journal of Molecular Cell Biology. 4(4). 221–230. 87 indexed citations
13.
Eberhard, Daniel, Kathy E. O’Neill, Zoë D. Burke, & David Tosh. (2010). In Vitro Reprogramming of Pancreatic Cells to Hepatocytes. Methods in molecular biology. 636. 285–292. 5 indexed citations
14.
Eberhard, Daniel & Harald Jockusch. (2010). Clonal and territorial development of the pancreas as revealed by eGFP-labelled mouse chimeras. Cell and Tissue Research. 342(1). 31–38. 7 indexed citations
15.
Burke, Zoë D., Daniel Eberhard, Chia‐Ning Shen, et al.. (2010). Dexamethasone Treatment Induces the Reprogramming of Pancreatic Acinar Cells to Hepatocytes and Ductal Cells. PLoS ONE. 5(10). e13650–e13650. 26 indexed citations
16.
Eberhard, Daniel & Eckhard Lammert. (2009). The pancreatic β-cell in the islet and organ community. Current Opinion in Genetics & Development. 19(5). 469–475. 49 indexed citations
17.
Eberhard, Daniel & David Tosh. (2007). Molecular and Cellular Basis of Regeneration and Tissue Repair. Cellular and Molecular Life Sciences. 65(1). 33–40. 37 indexed citations
18.
Eberhard, Daniel & Harald Jockusch. (2004). Patterns of myocardial histogenesis as revealed by mouse chimeras. Developmental Biology. 278(2). 336–346. 13 indexed citations
19.
Eberhard, Daniel & Harald Jockusch. (2004). Intermingling versus clonal coherence during skeletal muscle development: Mosaicism in eGFP/nLacZ‐labeled mouse chimeras. Developmental Dynamics. 230(1). 69–78. 6 indexed citations
20.

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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