Wolfgang Deppert

8.4k total citations
201 papers, 7.0k citations indexed

About

Wolfgang Deppert is a scholar working on Oncology, Molecular Biology and Genetics. According to data from OpenAlex, Wolfgang Deppert has authored 201 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 132 papers in Oncology, 97 papers in Molecular Biology and 49 papers in Genetics. Recurrent topics in Wolfgang Deppert's work include Cancer-related Molecular Pathways (83 papers), Virus-based gene therapy research (44 papers) and Polyomavirus and related diseases (37 papers). Wolfgang Deppert is often cited by papers focused on Cancer-related Molecular Pathways (83 papers), Virus-based gene therapy research (44 papers) and Polyomavirus and related diseases (37 papers). Wolfgang Deppert collaborates with scholars based in Germany, United States and United Kingdom. Wolfgang Deppert's co-authors include Ella Kim, Lisa Wiesmüller, Daniel Speidel, Matthias Staufenbiel, Frank Große, Gernot Walter, Uwe Knippschild, Sonja Wolff, Ute M. Moll and Friedemann Janus and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Wolfgang Deppert

199 papers receiving 6.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wolfgang Deppert Germany 46 4.4k 4.0k 1.1k 806 778 201 7.0k
Ellen Fanning United States 51 5.9k 1.3× 2.8k 0.7× 2.0k 1.9× 766 1.0× 162 0.2× 137 8.4k
Bohdan Wasylyk France 61 9.1k 2.1× 3.3k 0.8× 2.1k 1.9× 1.8k 2.3× 304 0.4× 151 12.5k
Àngel Pellicer United States 51 8.5k 1.9× 2.8k 0.7× 2.9k 2.7× 1.2k 1.4× 478 0.6× 178 12.8k
Walter Eckhart United States 39 3.7k 0.8× 2.4k 0.6× 1.5k 1.4× 260 0.3× 193 0.2× 94 5.9k
Ted R. Hupp United Kingdom 48 6.2k 1.4× 4.5k 1.1× 523 0.5× 1.2k 1.5× 1.2k 1.5× 234 8.6k
Scott L. Weinrich United States 22 7.6k 1.7× 1.5k 0.4× 1.4k 1.3× 728 0.9× 1.6k 2.1× 36 12.6k
Matthias Dobbelstein Germany 44 4.7k 1.0× 2.7k 0.7× 996 0.9× 1.3k 1.6× 682 0.9× 129 6.1k
Jac A. Nickoloff United States 48 7.6k 1.7× 1.7k 0.4× 967 0.9× 1.2k 1.5× 249 0.3× 146 8.8k
Gernot Walter United States 47 4.5k 1.0× 1.8k 0.5× 1.4k 1.3× 245 0.3× 145 0.2× 108 6.3k
H. Michael Shepard United States 39 4.5k 1.0× 4.8k 1.2× 1.2k 1.1× 682 0.8× 388 0.5× 64 9.3k

Countries citing papers authored by Wolfgang Deppert

Since Specialization
Citations

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

Fields of papers citing papers by Wolfgang Deppert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wolfgang Deppert

This figure shows the co-authorship network connecting the top 25 collaborators of Wolfgang Deppert. A scholar is included among the top collaborators of Wolfgang Deppert 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 Wolfgang Deppert. Wolfgang Deppert 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.
Hardt, Olaf, et al.. (2023). Basal‐like mammary carcinomas stimulate cancer stem cell properties through AXL‐signaling to induce chemotherapy resistance. International Journal of Cancer. 152(9). 1916–1932. 4 indexed citations
2.
Otto, Benjamin, Christina Heinlein, Florian Wegwitz, et al.. (2012). Low‐grade and high‐grade mammary carcinomas in WAP‐T transgenic mice are independent entities distinguished by Met expression. International Journal of Cancer. 132(6). 1300–1310. 16 indexed citations
3.
Ziegler, Christine, et al.. (2009). Wild-Type p53 Enhances Efficiency of Simian Virus 40 Large-T-Antigen-Induced Cellular Transformation. Journal of Virology. 83(19). 10106–10118. 15 indexed citations
4.
Jannasch, Katharina, Christian Dullin, Christina Heinlein, et al.. (2009). Detection of different tumor growth kinetics in single transgenic mice with oncogene‐induced mammary carcinomas by flat‐panel volume computed tomography. International Journal of Cancer. 125(1). 62–70. 19 indexed citations
5.
6.
Baschuk, Nikola, Olaf Utermöhlen, Gabriele Warnecke, et al.. (2007). Interleukin-4 impairs granzyme-mediated cytotoxicity of Simian virus 40 large tumor antigen-specific CTL in BALB/c mice. Cancer Immunology Immunotherapy. 56(10). 1625–1636. 11 indexed citations
7.
Reimer, Raylene A., et al.. (2005). Cooperation between p53 and p130(Rb2) in induction of cellular senescence. Cell Death and Differentiation. 13(2). 324–334. 39 indexed citations
8.
Maritzen, Tanja, Jürgen Löhler, Wolfgang Deppert, & Uwe Knippschild. (2003). Casein kinase I delta (CKIδ) is involved in lymphocyte physiology. European Journal of Cell Biology. 82(7). 369–378. 28 indexed citations
9.
Hagel, Christian, et al.. (2002). Cytoplasmic localization of wild-type p53 in glioblastomas correlateswith expression of vimentin and glial fibrillary acidic protein. Neuro-Oncology. 4(3). 171–178. 36 indexed citations
10.
Deppert, Wolfgang, et al.. (2001). Mensch und Wirtschaft : Interdisziplinäre Beiträge zur Wirtschafts- und Unternehmensethik. 1 indexed citations
11.
Janus, Friedemann, et al.. (1999). Different Regulation of the p53 Core Domain Activities 3′-to-5′ Exonuclease and Sequence-Specific DNA Binding. Molecular and Cellular Biology. 19(3). 2155–2168. 43 indexed citations
12.
Hohenberg, Heinz, et al.. (1998). Cytoplasmic retention of mutant tsp53 is dependent on an intermediate filament protein (Vimentin) scaffold. Oncogene. 16(26). 3423–3434. 46 indexed citations
13.
Deppert, Wolfgang, et al.. (1996). Specific binding of MAR/SAR DNA-elements by mutant p53.. PubMed. 12(9). 1941–52. 37 indexed citations
14.
Zerrahn, Jens, et al.. (1996). Simian virus 40 small t antigen activates the carboxyl-terminal transforming p53-binding domain of large T antigen. Journal of Virology. 70(10). 6781–6789. 6 indexed citations
15.
Deppert, Wolfgang, et al.. (1995). Emergence of virus escape mutants after immunization with epitope vaccine. Journal of Virology. 69(11). 7147–7151. 32 indexed citations
16.
Richter, Wiltrud & Wolfgang Deppert. (1990). The cellular chromatin is an important target for SV40 large T antigen in maintaining the transformed phenotype. Virology. 174(2). 543–556. 8 indexed citations
17.
Deppert, Wolfgang, et al.. (1986). The kinase activity of SV40 large T antigen is mediated by a cellular kinase.. The EMBO Journal. 5(5). 883–889. 13 indexed citations
18.
Klockmann, U., Daniel F. Klessig, & Wolfgang Deppert. (1985). Similar regulation of the synthesis of adenovirus fiber and of simian virus 40-specific proteins encoded by the helper-defective Ad2+SV40 hybrid viruses Ad2+ND5 and Ad2+ND4del. Journal of Virology. 56(3). 821–829. 4 indexed citations
19.
Deppert, Wolfgang. (1981). Grundlagen einer Theorie der Systemzeiten. 6(2). 1–25. 1 indexed citations
20.
Deppert, Wolfgang, Ferdinand Hucho, & Horst Sund. (1973). Studies of Glutamate Dehydrogenase. European Journal of Biochemistry. 32(1). 76–82. 21 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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