Beate Kellert

1.4k total citations · 1 hit paper
7 papers, 1.1k citations indexed

About

Beate Kellert is a scholar working on Molecular Biology, Immunology and Rheumatology. According to data from OpenAlex, Beate Kellert has authored 7 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Immunology and 2 papers in Rheumatology. Recurrent topics in Beate Kellert's work include Cell death mechanisms and regulation (2 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (1 paper) and CRISPR and Genetic Engineering (1 paper). Beate Kellert is often cited by papers focused on Cell death mechanisms and regulation (2 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (1 paper) and CRISPR and Genetic Engineering (1 paper). Beate Kellert collaborates with scholars based in Germany, United Kingdom and Australia. Beate Kellert's co-authors include Martin Leverkus, Mike Hupe, Peter Geserick, Maria Feoktistova, Georg Häcker, Marion MacFarlane, Claudia Langlais, Kelvin Cain, Maryline Moulin and John Silke and has published in prestigious journals such as The Journal of Cell Biology, Molecular Cell and The Journal of Immunology.

In The Last Decade

Beate Kellert

7 papers receiving 1.1k citations

Hit Papers

cIAPs Block Ripoptosome Formation, a RIP1/Caspase-8 Conta... 2011 2026 2016 2021 2011 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Beate Kellert Germany 7 886 535 198 152 147 7 1.1k
Mike Hupe Germany 10 1.0k 1.2× 562 1.1× 247 1.2× 171 1.1× 171 1.2× 10 1.3k
Inge Bruggeman Belgium 7 1.1k 1.2× 531 1.0× 149 0.8× 187 1.2× 139 0.9× 10 1.3k
Sam Strickson United Kingdom 7 564 0.6× 439 0.8× 252 1.3× 121 0.8× 180 1.2× 10 894
Natalia Ronkina Germany 16 977 1.1× 406 0.8× 271 1.4× 92 0.6× 250 1.7× 24 1.4k
Alicia Algeciras-Schimnich United States 15 836 0.9× 564 1.1× 223 1.1× 178 1.2× 195 1.3× 21 1.3k
Matija Zelic United States 11 1.0k 1.2× 788 1.5× 193 1.0× 156 1.0× 133 0.9× 13 1.4k
Yinming Liang China 20 584 0.7× 621 1.2× 209 1.1× 129 0.8× 219 1.5× 76 1.4k
Sofie Van Huffel Belgium 8 695 0.8× 366 0.7× 335 1.7× 105 0.7× 140 1.0× 8 1.1k
Shreeram C. Nallar United States 21 450 0.5× 313 0.6× 197 1.0× 121 0.8× 275 1.9× 32 944
Daniel R. Beisner United States 10 594 0.7× 666 1.2× 126 0.6× 99 0.7× 191 1.3× 11 1.0k

Countries citing papers authored by Beate Kellert

Since Specialization
Citations

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

Fields of papers citing papers by Beate Kellert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Beate Kellert

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

All Works

7 of 7 papers shown
1.
Kellert, Beate, Georgia Metzgeroth, Claudia Haferlach, et al.. (2014). Identification and functional characterization of imatinib‐sensitive DTD1‐PDGFRB and CCDC88C‐PDGFRB fusion genes in eosinophilia‐associated myeloid/lymphoid neoplasms. Genes Chromosomes and Cancer. 53(5). 411–421. 15 indexed citations
2.
Michel, Julia, Kai Schledzewski, Carsten Sticht, et al.. (2013). Identification of the novel differentiation marker MS4A8B and its murine homolog MS4A8A in colonic epithelial cells lost during neoplastic transformation in human colon. Cell Death and Disease. 4(1). e469–e469. 17 indexed citations
3.
Panayotova‐Dimitrova, Diana, Maria Feoktistova, Beate Kellert, et al.. (2013). cFLIP Regulates Skin Homeostasis and Protects against TNF-Induced Keratinocyte Apoptosis. Cell Reports. 5(2). 397–408. 61 indexed citations
4.
Lehner, Manfred, Beate Kellert, Martina Schmid, et al.. (2012). Autocrine TNF Is Critical for the Survival of Human Dendritic Cells by Regulating BAK, BCL-2, and FLIPL. The Journal of Immunology. 188(10). 4810–4818. 18 indexed citations
5.
Feoktistova, Maria, Peter Geserick, Beate Kellert, et al.. (2011). cIAPs Block Ripoptosome Formation, a RIP1/Caspase-8 Containing Intracellular Cell Death Complex Differentially Regulated by cFLIP Isoforms. Molecular Cell. 43(3). 449–463. 687 indexed citations breakdown →
6.
Hirrlinger, Johannes, Anja Scheller, Petra G. Hirrlinger, et al.. (2009). Split-Cre Complementation Indicates Coincident Activity of Different Genes In Vivo. PLoS ONE. 4(1). e4286–e4286. 127 indexed citations
7.
Geserick, Peter, Mike Hupe, Maryline Moulin, et al.. (2009). Cellular IAPs inhibit a cryptic CD95-induced cell death by limiting RIP1 kinase recruitment. The Journal of Cell Biology. 187(7). 1037–1054. 198 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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