Michael Düwel

814 total citations
10 papers, 652 citations indexed

About

Michael Düwel is a scholar working on Cancer Research, Molecular Biology and Immunology. According to data from OpenAlex, Michael Düwel has authored 10 papers receiving a total of 652 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cancer Research, 6 papers in Molecular Biology and 6 papers in Immunology. Recurrent topics in Michael Düwel's work include NF-κB Signaling Pathways (5 papers), interferon and immune responses (2 papers) and Cancer, Hypoxia, and Metabolism (2 papers). Michael Düwel is often cited by papers focused on NF-κB Signaling Pathways (5 papers), interferon and immune responses (2 papers) and Cancer, Hypoxia, and Metabolism (2 papers). Michael Düwel collaborates with scholars based in Germany, United States and Belgium. Michael Düwel's co-authors include Daniel Krappmann, Jürgen Ruland, Uta Ferch, Ernst Ungewickell, Andreas Gewies, Christian Peschel, Bryant G. Darnay, Andrea Oeckinghaus, Mathijs Baens and Peter Marynen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Experimental Medicine.

In The Last Decade

Michael Düwel

10 papers receiving 646 citations

Peers

Michael Düwel

MB

IMMUN

CR

ONCOL

PFM

Naiyan Zeng China

Éric Cabannes France

Huifeng Niu United States

Alyssa Bouska United States

Anja Deutzmann United States

Piao Lo United States

Valentina Serafin Italy

Anka Bric United States

Michele M. Johnson United States

Tara M. Love United States

Naiyan Zeng China

Michael Düwel

260 ×0.8

MB

163 ×0.5

IMMUN

118 ×0.4

CR

185 ×1.2

ONCOL

177 ×1.3

PFM

Citations per year, relative to Michael Düwel Michael Düwel (= 1×) peers Naiyan Zeng

Countries citing papers authored by Michael Düwel

Since Specialization

Citations

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

Fields of papers citing papers by Michael Düwel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Düwel

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

All Works

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10 of 10 papers shown

1.

Schilling, Daniela, Michael Düwel, M. Molls, & Gabriele Multhoff. (2012). Radiosensitization of wildtype p53 cancer cells by the MDM2-inhibitor PXN727 is associated with altered heat shock protein 70 (Hsp70) levels. Cell Stress and Chaperones. 18(2). 183–191. 15 indexed citations

2.

Düwel, Michael, Kamyar Hadian, & Daniel Krappmann. (2010). Ubiquitin Conjugation and Deconjugation in NF-κB Signaling. Sub-cellular biochemistry. 54. 88–99. 8 indexed citations

3.

Eitelhuber, Andrea C., Sebastian C. Warth, Michael Düwel, et al.. (2010). Dephosphorylation of Carma1 by PP2A negatively regulates T‐cell activation. The EMBO Journal. 30(3). 594–605. 62 indexed citations

4.

Nagel, Daniel, Matthias Pfeifer, Michael Grau, et al.. (2010). Critical role of PI3K signaling for NF-κB–dependent survival in a subset of activated B-cell–like diffuse large B-cell lymphoma cells. Proceedings of the National Academy of Sciences. 108(1). 272–277. 111 indexed citations

5.

Ferch, Uta, Andreas Gewies, Michael Düwel, et al.. (2009). Inhibition of MALT1 protease activity is selectively toxic for activated B cell–like diffuse large B cell lymphoma cells. The Journal of Experimental Medicine. 206(12). 2851–2851. 1 indexed citations

6.

Eitelhuber, Andrea C., et al.. (2009). COP9 signalosome controls the Carma1–Bcl10–Malt1 complex upon T‐cell stimulation. EMBO Reports. 10(6). 642–648. 27 indexed citations

7.

Ferch, Uta, Andreas Gewies, Michael Düwel, et al.. (2009). Inhibition of MALT1 protease activity is selectively toxic for activated B cell–like diffuse large B cell lymphoma cells. The Journal of Experimental Medicine. 206(11). 2313–2320. 161 indexed citations

8.

Düwel, Michael, Andrea Oeckinghaus, Mathijs Baens, et al.. (2009). A20 Negatively Regulates T Cell Receptor Signaling to NF-κB by Cleaving Malt1 Ubiquitin Chains. The Journal of Immunology. 182(12). 7718–7728. 193 indexed citations

9.

Düwel, Michael & Ernst Ungewickell. (2006). Clathrin-dependent Association of CVAK104 with Endosomes and theTrans-Golgi Network. Molecular Biology of the Cell. 17(10). 4513–4525. 32 indexed citations

10.

Alves, Jürgen, et al.. (2003). Molecular and Functional Characterization of Clathrin- and AP-2-binding Determinants within a Disordered Domain of Auxilin. Journal of Biological Chemistry. 278(28). 25357–25368. 42 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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