Guntram Suske

9.2k total citations · 4 hit papers
89 papers, 7.8k citations indexed

About

Guntram Suske is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Guntram Suske has authored 89 papers receiving a total of 7.8k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Molecular Biology, 15 papers in Immunology and 14 papers in Genetics. Recurrent topics in Guntram Suske's work include Genomics and Chromatin Dynamics (18 papers), RNA Research and Splicing (16 papers) and Cancer-related gene regulation (12 papers). Guntram Suske is often cited by papers focused on Genomics and Chromatin Dynamics (18 papers), RNA Research and Splicing (16 papers) and Cancer-related gene regulation (12 papers). Guntram Suske collaborates with scholars based in Germany, United States and Netherlands. Guntram Suske's co-authors include Miguel Beato, Sjaak Philipsen, Gustav Hagen, Susanne Müller, Jörg Dennig, Elspeth A. Bruford, Alexandra Sapetschnig, Harald Braun, Luigi Lania and Barbara Majello and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Guntram Suske

88 papers receiving 7.7k citations

Hit Papers

The Sp-family of transcri... 1992 2026 2003 2014 1999 1994 1992 1999 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guntram Suske Germany 42 5.8k 1.2k 1.0k 933 820 89 7.8k
Roshantha A.S. Chandraratna United States 49 5.4k 0.9× 2.0k 1.7× 731 0.7× 1.3k 1.4× 597 0.7× 155 7.7k
Marian L. Waterman United States 44 5.5k 0.9× 1.0k 0.9× 1.1k 1.1× 789 0.8× 983 1.2× 75 7.2k
Yvan de Launoit France 48 5.2k 0.9× 1.5k 1.3× 1.3k 1.3× 949 1.0× 1.2k 1.4× 161 8.1k
Corey Largman United States 48 5.9k 1.0× 1.0k 0.9× 846 0.8× 964 1.0× 752 0.9× 121 8.4k
Claudio Sette Italy 54 6.5k 1.1× 797 0.7× 858 0.9× 1.1k 1.2× 1.3k 1.6× 179 8.9k
Robert P. Wersto United States 48 4.0k 0.7× 841 0.7× 1.9k 1.9× 1.4k 1.5× 978 1.2× 91 7.1k
Sjaak Philipsen Netherlands 45 6.1k 1.0× 1.2k 1.0× 716 0.7× 933 1.0× 813 1.0× 122 8.2k
Eugenio Santos Spain 45 5.8k 1.0× 1.0k 0.9× 2.2k 2.2× 802 0.9× 1.1k 1.4× 154 8.3k
Ludger Klein‐Hitpaß Germany 48 4.9k 0.8× 2.2k 1.8× 1.3k 1.3× 1.5k 1.6× 920 1.1× 160 8.3k
Douglas S. Darling United States 41 4.1k 0.7× 1.6k 1.3× 1.6k 1.6× 564 0.6× 1.4k 1.8× 90 6.5k

Countries citing papers authored by Guntram Suske

Since Specialization
Citations

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

Fields of papers citing papers by Guntram Suske

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guntram Suske

This figure shows the co-authorship network connecting the top 25 collaborators of Guntram Suske. A scholar is included among the top collaborators of Guntram Suske 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 Guntram Suske. Guntram Suske 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.
Stielow, Bastian, et al.. (2018). Transcription factor Sp2 potentiates binding of the TALE homeoproteins Pbx1:Prep1 and the histone-fold domain protein Nf-y to composite genomic sites. Journal of Biological Chemistry. 293(50). 19250–19262. 7 indexed citations
2.
Meinders, Marjolein, Harmen J.G. van de Werken, Mark Hoogenboezem, et al.. (2014). Sp1/Sp3 transcription factors regulate hallmarks of megakaryocyte maturation and platelet formation and function. Blood. 125(12). 1957–1967. 46 indexed citations
3.
Meißner, Markus, Carmen Urbich, Kerstin Reisinger, et al.. (2003). PPARα Activators Inhibit Vascular Endothelial Growth Factor Receptor-2 Expression by Repressing Sp1-Dependent DNA Binding and Transactivation. Circulation Research. 94(3). 324–332. 93 indexed citations
4.
Sapetschnig, Alexandra, Grigore Rischitor, Harald Braun, et al.. (2002). Transcription factor Sp3 is silenced through SUMO modification by PIAS1. The EMBO Journal. 21(19). 5206–5215. 226 indexed citations
5.
Song, Jun, Guntram Suske, Christian Geltinger, et al.. (2001). Characterization and promoter analysis of the mouse gene for transcription factor Sp4. Gene. 264(1). 19–27. 24 indexed citations
6.
Ghayor, Chafik, Christos Chadjichristos, Leena Ala‐Kokko, et al.. (2001). SP3 Represses the SP1-mediated Transactivation of the HumanCOL2A1 Gene in Primary and De-differentiated Chondrocytes. Journal of Biological Chemistry. 276(40). 36881–36895. 80 indexed citations
7.
Nord, Magnus, Tobias N. Cassel, Harald Braun, & Guntram Suske. (2000). Regulation of the Clara Cell Secretory Protein/Uteroglobin Promoter in Lung. Annals of the New York Academy of Sciences. 923(1). 154–165. 35 indexed citations
8.
Cassel, Tobias N., Guntram Suske, & Magnus Nord. (2000). C/EBPα and TTF‐1 Synergistically Transactivate the Clara Cell Secretory Protein Gene. Annals of the New York Academy of Sciences. 923(1). 300–302. 11 indexed citations
9.
Müller, Susanne, Alex Maas, Tahmina Islam, et al.. (1999). Synergistic Activation of the Human Btk Promoter by Transcription Factors Sp1/3 and PU.1. Biochemical and Biophysical Research Communications. 259(2). 364–369. 21 indexed citations
10.
Braun, Harald & Guntram Suske. (1998). Combinatorial Action of HNF3 and Sp Family Transcription Factors in the Activation of the Rabbit Uteroglobin/CC10 Promoter. Journal of Biological Chemistry. 273(16). 9821–9828. 58 indexed citations
13.
Dennig, Jörg, Miguel Beato, & Guntram Suske. (1996). An inhibitor domain in Sp3 regulates its glutamine-rich activation domains.. The EMBO Journal. 15(20). 5659–5667. 196 indexed citations
14.
Vogel, Lotte K., Guntram Suske, Miguel Beato, Ove Norén, & Hans Sjöström. (1993). Uteroglobin, an apically secreted protein of the uterine epithelium, is secreted non‐polarized from MDCK cells and mainly basolaterally from Caco‐2 cell. FEBS Letters. 330(3). 293–296. 8 indexed citations
15.
Peter, W Kinyanjui, et al.. (1992). Interchain cysteine bridges control entry of progesterone to the central cavity of the uteroglobin dimer. Protein Engineering Design and Selection. 5(4). 351–359. 16 indexed citations
16.
Slater, Emily P., et al.. (1990). The Uteroglobin Promoter Contains a Noncanonical Estrogen Responsive Element. Molecular Endocrinology. 4(4). 604–610. 85 indexed citations
17.
Scheidereit, Claus, Dietmar von der Ahe, Andrew C.B. Cato, et al.. (1989). Protein-DNA Interactions at Steroid Hormone Regulated Genes. Endocrine Research. 15(4). 417–440. 15 indexed citations
18.
Suske, Guntram, et al.. (1989). Non-radioactive method to visualize specific DNA-protein interactions in the band shift assay. Nucleic Acids Research. 17(11). 4405–4405. 14 indexed citations
20.
Scheidereit, Claus, Dietmar von der Ahe, Andrew C.B. Cato, et al.. (1986). Mechanism of gene regulation by steroid hormones. Journal of Steroid Biochemistry. 24(1). 19–24. 34 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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