Ute Scheffer

876 total citations
34 papers, 623 citations indexed

About

Ute Scheffer is a scholar working on Molecular Biology, Immunology and Virology. According to data from OpenAlex, Ute Scheffer has authored 34 papers receiving a total of 623 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 5 papers in Immunology and 3 papers in Virology. Recurrent topics in Ute Scheffer's work include RNA and protein synthesis mechanisms (14 papers), DNA and Nucleic Acid Chemistry (11 papers) and Advanced biosensing and bioanalysis techniques (8 papers). Ute Scheffer is often cited by papers focused on RNA and protein synthesis mechanisms (14 papers), DNA and Nucleic Acid Chemistry (11 papers) and Advanced biosensing and bioanalysis techniques (8 papers). Ute Scheffer collaborates with scholars based in Germany, Japan and Bangladesh. Ute Scheffer's co-authors include Michael Göbel, Wernér E.G. Müller, Stefan Vonhoff, Sven Klußmann, Zeev Pancer, Gisbert Schneider, Heike Schäcke, Claudio Toniolo, Alessandro Scarso and Fernando Formaggio and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Biochemical and Biophysical Research Communications.

In The Last Decade

Ute Scheffer

31 papers receiving 602 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ute Scheffer Germany 14 440 181 65 56 53 34 623
Alexander A. Szewczak United States 17 962 2.2× 111 0.6× 30 0.5× 57 1.0× 136 2.6× 29 1.2k
Jared T. Hammill United States 14 587 1.3× 180 1.0× 81 1.2× 25 0.4× 14 0.3× 22 825
Jenn-Kang Hwang Taiwan 14 663 1.5× 138 0.8× 32 0.5× 32 0.6× 25 0.5× 18 918
James A. Van Deventer United States 16 731 1.7× 160 0.9× 28 0.4× 81 1.4× 64 1.2× 32 927
Samuel Toba United States 8 378 0.9× 126 0.7× 51 0.8× 15 0.3× 13 0.2× 10 509
Enrique Marcos Spain 14 606 1.4× 116 0.6× 44 0.7× 28 0.5× 18 0.3× 24 794
Burckhard Seelig United States 17 1.3k 2.9× 202 1.1× 48 0.7× 68 1.2× 20 0.4× 34 1.5k
David F. Green United States 14 400 0.9× 67 0.4× 48 0.7× 16 0.3× 16 0.3× 19 521
K.V. Radha Kishan India 13 366 0.8× 60 0.3× 52 0.8× 43 0.8× 17 0.3× 22 600
Leonard M. G. Chavas Japan 16 523 1.2× 123 0.7× 31 0.5× 37 0.7× 81 1.5× 43 785

Countries citing papers authored by Ute Scheffer

Since Specialization
Citations

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

Fields of papers citing papers by Ute Scheffer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ute Scheffer

This figure shows the co-authorship network connecting the top 25 collaborators of Ute Scheffer. A scholar is included among the top collaborators of Ute Scheffer 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 Ute Scheffer. Ute Scheffer 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.
Scheffer, Ute, et al.. (2025). Click Conjugates of Artificial Ribonucleases: Sequence Specific Cleavage with Multiple Turnover. Chemistry - A European Journal. 31(30). e202500451–e202500451.
2.
Kaiser, Frank J., Burkhard Endeward, Alberto Collauto, et al.. (2022). Spin‐Labeled Riboswitch Synthesized from a Protected TPA Phosphoramidite Building Block. Chemistry - A European Journal. 28(56). e202201822–e202201822. 4 indexed citations
3.
Scheffer, Ute, et al.. (2020). Redirection of miRNA‐Argonaute Complexes to Specific Target Sites by Synthetic Adaptor Molecules. Chemistry & Biodiversity. 17(7). e2000272–e2000272. 2 indexed citations
4.
Scheffer, Ute, et al.. (2019). Site-Specific Cleavage of RNAs Derived from the PIM1 3′-UTR by a Metal-Free Artificial Ribonuclease. Molecules. 24(4). 807–807. 13 indexed citations
5.
Scheffer, Ute, et al.. (2018). Phosphoramidite building blocks with protected nitroxides for the synthesis of spin-labeled DNA and RNA. Beilstein Journal of Organic Chemistry. 14. 1563–1569. 5 indexed citations
6.
Stark, Sebastian, et al.. (2014). Fragment based search for small molecule inhibitors of HIV-1 Tat-TAR. Bioorganic & Medicinal Chemistry Letters. 24(24). 5576–5580. 31 indexed citations
7.
Ullrich, Stefan, et al.. (2011). Cleavage of Phosphodiesters and of DNA by a Bis(guanidinium)naphthol Acting as a Metal‐Free Anion Receptor. ChemBioChem. 12(8). 1223–1229. 18 indexed citations
8.
Krebs, Andreas, Ursula Dietrich, Jan Ferner, et al.. (2007). Tripeptides from Synthetic Amino Acids Block the Tat–TAR Association and Slow Down HIV Spread in Cell Cultures. ChemBioChem. 8(15). 1850–1856. 15 indexed citations
9.
Schüller, Andreas, Uli Fechner, Yusuf Tanrıkulu, et al.. (2007). The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA. Journal of Computer-Aided Molecular Design. 22(2). 59–68. 19 indexed citations
10.
Krebs, Andreas, et al.. (2007). Classification and Prediction of Tripeptides Inhibiting HIV-1 Tat/TAR-RNA Interaction Using a Self-Organizing Map. Letters in Drug Design & Discovery. 4(6). 410–416.
11.
Tanrıkulu, Yusuf, Manuel Nietert, Ute Scheffer, et al.. (2007). Scaffold Hopping by “Fuzzy” Pharmacophores and its Application to RNA Targets. ChemBioChem. 8(16). 1932–1936. 39 indexed citations
12.
Morgner, Nina, H.-D. Barth, Thorsten L. Schmidt, et al.. (2007). Detecting Specific Ligand Binding to Nucleic Acids: A Test for Ultrasoft Laser Mass Spectrometry. Zeitschrift für Physikalische Chemie. 221(5). 689–704. 7 indexed citations
13.
Renner, Steffen, et al.. (2005). New Inhibitors of the Tat–TAR RNA Interaction Found with a “Fuzzy” Pharmacophore Model. ChemBioChem. 6(6). 1119–1125. 33 indexed citations
14.
Scheffer, Ute, et al.. (2004). Fluorescence-Based On-Line Detection as an Analytical Tool in RNA Electrophoresis. Humana Press eBooks. 288. 261–272. 1 indexed citations
15.
Scheffer, Ute, et al.. (2002). E-Learning : die Revolution des Lernens gewinnbringend einsetzen. Klett-Cotta eBooks. 6 indexed citations
16.
Müller, Wernér E.G., et al.. (1997). Interaction of prion protein mRNA with CBP35 and other cellular proteins Possible implications for prion replication and age-dependent changes. Archives of Gerontology and Geriatrics. 25(1). 41–58. 7 indexed citations
17.
Pancer, Zeev, Michael Kruse, Heike Schäcke, et al.. (1996). Polymorphism in the Immunoglobulin-like Domains of the Receptor Tyrosine Kinase from the SpongeGeodia Cydonium. Cell adhesion and communications/Cell adhesion and communication/Cell adhesion & communication. 4(4-5). 327–339. 42 indexed citations
18.
Kuusksalu, Anne, Erkki Truve, Anu Aaspõllu, et al.. (1995). Impairment of intracellular antiviral defense with age: Age-dependent changes in expression of interferon-induced and double-stranded RNA-activated 2–5A synthetase in rat. Mechanisms of Ageing and Development. 78(2). 103–115. 4 indexed citations
19.
Scheffer, Ute, et al.. (1995). Interaction of 68–kDa TAR RNA-binding protein and other cellular proteins with rpion protein-RNA stem-loop. Journal of NeuroVirology. 1(5-6). 391–398. 6 indexed citations
20.

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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