Daniela Eggle

1.1k total citations
19 papers, 910 citations indexed

About

Daniela Eggle is a scholar working on Molecular Biology, Cancer Research and Immunology. According to data from OpenAlex, Daniela Eggle has authored 19 papers receiving a total of 910 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 7 papers in Cancer Research and 6 papers in Immunology. Recurrent topics in Daniela Eggle's work include Molecular Biology Techniques and Applications (4 papers), NF-κB Signaling Pathways (3 papers) and Gene expression and cancer classification (3 papers). Daniela Eggle is often cited by papers focused on Molecular Biology Techniques and Applications (4 papers), NF-κB Signaling Pathways (3 papers) and Gene expression and cancer classification (3 papers). Daniela Eggle collaborates with scholars based in Germany, United States and Switzerland. Daniela Eggle's co-authors include Stefan Klostermann, Ulrich H. Weidle, Joachim L. Schultze, Werner Scheuer, Hannes Stockinger, Guido W.M. Swart, Svenja Debey‐Pascher, Alexey Popov, Achim Krüger and Sabine Claßen and has published in prestigious journals such as Journal of Clinical Investigation, Blood and Bioinformatics.

In The Last Decade

Daniela Eggle

19 papers receiving 897 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniela Eggle Germany 14 465 315 225 211 73 19 910
Melanie Mediavilla-Varela United States 12 379 0.8× 261 0.8× 270 1.2× 81 0.4× 55 0.8× 28 860
Sabine Claßen Germany 13 283 0.6× 636 2.0× 287 1.3× 89 0.4× 37 0.5× 17 996
Jason Walker United States 12 469 1.0× 303 1.0× 168 0.7× 146 0.7× 50 0.7× 21 936
Kouichirou Tahara Japan 15 457 1.0× 713 2.3× 506 2.2× 124 0.6× 56 0.8× 23 1.1k
Jean‐René Pallandre France 16 314 0.7× 585 1.9× 484 2.2× 117 0.6× 83 1.1× 28 1.1k
Charles Link United States 18 296 0.6× 277 0.9× 391 1.7× 71 0.3× 43 0.6× 40 983
Zhibo Shen China 16 473 1.0× 232 0.7× 277 1.2× 335 1.6× 44 0.6× 32 896
Julia Feichtinger Austria 18 431 0.9× 179 0.6× 120 0.5× 119 0.6× 31 0.4× 31 696
Matouš Hrdinka Czechia 18 693 1.5× 432 1.4× 231 1.0× 174 0.8× 89 1.2× 34 1.0k
Deblina Raychaudhuri India 11 408 0.9× 604 1.9× 461 2.0× 173 0.8× 102 1.4× 17 1.2k

Countries citing papers authored by Daniela Eggle

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Eggle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela Eggle

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

All Works

19 of 19 papers shown
1.
Weidle, Ulrich H., Stefan Klostermann, Daniela Eggle, & Achim Krüger. (2011). Interleukin 6/interleukin 6 receptor interaction and its role as a therapeutic target for treatment of cachexia and cancer.. PubMed. 7(6). 287–302. 57 indexed citations
2.
Weidle, Ulrich H., Daniela Eggle, Stefan Klostermann, & Guido W.M. Swart. (2011). ALCAM/CD166: cancer-related issues.. PubMed. 7(5). 231–43. 113 indexed citations
3.
4.
Claßen, Sabine, Svenja Debey‐Pascher, Daniela Eggle, et al.. (2010). Application of T cell-based transcriptomics to identify three candidate biomarkers for monitoring anti-TGFβR therapy. Pharmacogenetics and Genomics. 20(3). 147–156. 11 indexed citations
5.
Debey‐Pascher, Svenja, Sabine Claßen, Daniela Eggle, et al.. (2010). Bead Array–Based microRNA Expression Profiling of Peripheral Blood and the Impact of Different RNA Isolation Approaches. Journal of Molecular Diagnostics. 12(3). 335–344. 22 indexed citations
6.
Küntzer, Jan, Daniela Eggle, Hans‐Peter Lenhof, Helmut Burtscher, & Stefan Klostermann. (2010). The Roche Cancer Genome Database (RCGDB). Human Mutation. 31(4). 407–413. 13 indexed citations
7.
Küntzer, Jan, Daniela Eggle, Stefan Klostermann, & Helmut Burtscher. (2010). Human variation databases. Database. 2010(0). baq015–baq015. 17 indexed citations
8.
Weidle, Ulrich H., Werner Scheuer, Daniela Eggle, Stefan Klostermann, & Hannes Stockinger. (2010). Cancer-related issues of CD147.. PubMed. 7(3). 157–69. 150 indexed citations
9.
Beyer, Marc, Julia Karbach, Michael R. Mallmann, et al.. (2009). Cancer Vaccine Enhanced, Non–Tumor-Reactive CD8+ T Cells Exhibit a Distinct Molecular Program Associated with “Division Arrest Anergy”. Cancer Research. 69(10). 4346–4354. 12 indexed citations
10.
Eggle, Daniela, Svenja Debey‐Pascher, Marc Beyer, & Joachim L. Schultze. (2009). The development of a comparison approach for Illumina bead chips unravels unexpected challenges applying newest generation microarrays. BMC Bioinformatics. 10(1). 186–186. 4 indexed citations
11.
Kern, Michaela, Alexey Popov, Kai Scholz, et al.. (2009). Virally Infected Mouse Liver Endothelial Cells Trigger CD8+ T-Cell Immunity. Gastroenterology. 138(1). 336–346. 57 indexed citations
12.
Debey‐Pascher, Svenja, Daniela Eggle, & Joachim L. Schultze. (2009). RNA Stabilization of Peripheral Blood and Profiling by Bead Chip Analysis. Methods in molecular biology. 496. 175–210. 20 indexed citations
13.
Pallasch, Christian P., Michaela Patz, Yoon Jung Park, et al.. (2009). miRNA deregulation by epigenetic silencing disrupts suppression of the oncogene PLAG1 in chronic lymphocytic leukemia. Blood. 114(15). 3255–3264. 118 indexed citations
14.
Weidle, Ulrich H., Daniela Eggle, & Stefan Klostermann. (2009). L1-CAM as a target for treatment of cancer with monoclonal antibodies.. PubMed. 29(12). 4919–31. 38 indexed citations
15.
Claßen, Sabine, Thomas Zander, Daniela Eggle, et al.. (2007). Human Resting CD4+ T Cells Are Constitutively Inhibited by TGFβ under Steady-State Conditions. The Journal of Immunology. 178(11). 6931–6940. 32 indexed citations
16.
Chemnitz, Jens M., Daniela Eggle, Julia Driesen, et al.. (2007). RNA fingerprints provide direct evidence for the inhibitory role of TGFβ and PD-1 on CD4+ T cells in Hodgkin lymphoma. Blood. 110(9). 3226–3233. 66 indexed citations
17.
Schultze, Joachim L. & Daniela Eggle. (2007). IlluminaGUI: Graphical User Interface for analyzing gene expression data generated on the Illumina platform. Bioinformatics. 23(11). 1431–1433. 12 indexed citations
18.
Popov, Alexey, Zeinab Abdullah, Claudia Wickenhauser, et al.. (2006). Indoleamine 2,3-dioxygenase–expressing dendritic cells form suppurative granulomas following Listeria monocytogenes infection. Journal of Clinical Investigation. 116(12). 3160–3170. 121 indexed citations
19.
Santos, Carlos, Daniela Eggle, & David J. States. (2004). Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction. Computer applications in the biosciences. 21(8). 1653–1658. 23 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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