Uli Schmitz

1.6k total citations · 1 hit paper
28 papers, 948 citations indexed

About

Uli Schmitz is a scholar working on Molecular Biology, Infectious Diseases and Spectroscopy. According to data from OpenAlex, Uli Schmitz has authored 28 papers receiving a total of 948 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 6 papers in Infectious Diseases and 6 papers in Spectroscopy. Recurrent topics in Uli Schmitz's work include RNA and protein synthesis mechanisms (8 papers), DNA and Nucleic Acid Chemistry (7 papers) and Hepatitis B Virus Studies (5 papers). Uli Schmitz is often cited by papers focused on RNA and protein synthesis mechanisms (8 papers), DNA and Nucleic Acid Chemistry (7 papers) and Hepatitis B Virus Studies (5 papers). Uli Schmitz collaborates with scholars based in United States, Czechia and Belgium. Uli Schmitz's co-authors include Thomas Leroy James, Seng‐Lai Tan, Anil Kumar, Nikolai B. Ulyanov, Peter Walter, Gerald Zon, T. L. James, Robert J. Keenan, Anil Kumar and Peter J. Lukavsky and has published in prestigious journals such as Science, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Uli Schmitz

28 papers receiving 925 citations

Hit Papers

Accelerating antiviral drug discovery: lessons from COVID-19 2023 2026 2024 2025 2023 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Uli Schmitz United States 20 665 150 127 123 120 28 948
Renzo Bazzo Italy 19 1.3k 1.9× 167 1.1× 280 2.2× 218 1.8× 135 1.1× 38 1.9k
Adrien Favier France 19 681 1.0× 97 0.6× 143 1.1× 40 0.3× 118 1.0× 46 1.2k
Stephanie A. Leavitt United States 17 837 1.3× 399 2.7× 70 0.6× 27 0.2× 93 0.8× 20 1.6k
Yuan Hu United States 15 444 0.7× 80 0.5× 81 0.6× 58 0.5× 60 0.5× 40 702
Christopher T. Lemke Canada 15 291 0.4× 287 1.9× 30 0.2× 90 0.7× 58 0.5× 27 647
Fareed Aboul‐ela United Kingdom 25 2.9k 4.4× 214 1.4× 132 1.0× 89 0.7× 73 0.6× 43 3.3k
Alexey V. Ustinov Russia 16 415 0.6× 90 0.6× 67 0.5× 31 0.3× 110 0.9× 96 1.1k
José Gallego Spain 23 1.1k 1.7× 109 0.7× 27 0.2× 96 0.8× 58 0.5× 50 1.4k
Michael Caffrey United States 29 1.2k 1.7× 494 3.3× 111 0.9× 36 0.3× 511 4.3× 94 2.1k
Allen D. Kline United States 18 1.0k 1.5× 74 0.5× 399 3.1× 79 0.6× 80 0.7× 21 1.4k

Countries citing papers authored by Uli Schmitz

Since Specialization
Citations

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

Fields of papers citing papers by Uli Schmitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Uli Schmitz

This figure shows the co-authorship network connecting the top 25 collaborators of Uli Schmitz. A scholar is included among the top collaborators of Uli Schmitz 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 Uli Schmitz. Uli Schmitz 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.
Delft, Annette von, Matthew D. Hall, Ann D. Kwong, et al.. (2023). Accelerating antiviral drug discovery: lessons from COVID-19. Nature Reviews Drug Discovery. 22(7). 585–603. 98 indexed citations breakdown →
2.
Perry, Jason K., T.C. Appleby, John P. Bilello, et al.. (2021). An atomistic model of the coronavirus replication-transcription complex as a hexamer assembled around nsp15. Journal of Biological Chemistry. 297(4). 101218–101218. 29 indexed citations
3.
Paulsen, Janet L., Haoyu S. Yu, Dan Sindhikara, et al.. (2020). Evaluation of Free Energy Calculations for the Prioritization of Macrocycle Synthesis. Journal of Chemical Information and Modeling. 60(7). 3489–3498. 14 indexed citations
4.
Jordan, Robert, Tetsuya Kobayashi, Ryan A. Dick, et al.. (2019). Anti-HBV activity of retinoid drugs in vitro versus in vivo. Antiviral Research. 169. 104538–104538. 5 indexed citations
5.
Boyce, S.E., Neeraj Tirunagari, Anita Niedziela‐Majka, et al.. (2014). Structural and Regulatory Elements of HCV NS5B Polymerase – β-Loop and C-Terminal Tail – Are Required for Activity of Allosteric Thumb Site II Inhibitors. PLoS ONE. 9(1). e84808–e84808. 27 indexed citations
6.
Hebner, Christy M., Bin Han, Katherine M. Brendza, et al.. (2012). The HCV Non-Nucleoside Inhibitor Tegobuvir Utilizes a Novel Mechanism of Action to Inhibit NS5B Polymerase Function. PLoS ONE. 7(6). e39163–e39163. 32 indexed citations
7.
Bryson, Paul D., Nam‐Joon Cho, Shirit Einav, et al.. (2010). A small molecule inhibits HCV replication and alters NS4B's subcellular distribution. Antiviral Research. 87(1). 1–8. 32 indexed citations
8.
Schmitz, Uli & Seng‐Lai Tan. (2008). NS5A - From Obscurity to New Target for HCV Therapy. Recent Patents on Anti-Infective Drug Discovery. 3(2). 77–92. 64 indexed citations
9.
James, Thomas Leroy, Volker Dötsch, & Uli Schmitz. (2001). Nuclear magnetic resonance of biological macromolecules. Academic Press eBooks. 19 indexed citations
10.
Zhang, Wentao, et al.. (2001). A novel dicationic polyamide ligand binds in the DNA minor groove as a dimer. FEBS Letters. 509(1). 85–89. 9 indexed citations
11.
Schmitz, Uli, Thomas Leroy James, Peter J. Lukavsky, & Peter Walter. (1999). Structure of the most conserved internal loop in SRP RNA.. Nature Structural Biology. 6(7). 634–638. 33 indexed citations
12.
Schmitz, Uli, Alessandro Donati, Thomas Leroy James, Nikolai B. Ulyanov, & Letitia J. Yao. (1998). Small structural ensembles for a 17-nucleotide mimic of the tRNA TΨC-loop via fitting dipolar relaxation rates with the quadratic programming algorithm. Biopolymers. 46(5). 329–342. 12 indexed citations
13.
Yao, Letitia J., Thomas Leroy James, James T. Kealey, Daniel V. Santi, & Uli Schmitz. (1997). The dynamic NMR structure of the TΨC-loop: Implications for the specificity of tRNA methylation. Journal of Biomolecular NMR. 9(3). 229–244. 18 indexed citations
14.
Schmitz, Uli, Douglas Freymann, Thomas Leroy James, et al.. (1996). NMR studies of the most conserved RNA domain of the mammalian signal recognition particle (SRP).. PubMed. 2(12). 1213–27. 18 indexed citations
15.
Schmitz, Uli & Thomas Leroy James. (1995). [1] How to generate accurate solution structures of double-helical nucleic acid fragments using nuclear magnetic resonance and restrained molecular dynamics. Methods in enzymology on CD-ROM/Methods in enzymology. 261. 3–44. 43 indexed citations
16.
Ulyanov, Nikolai B., Uli Schmitz, Anil Kumar, & T. L. James. (1995). Probability assessment of conformational ensembles: sugar repuckering in a DNA duplex in solution. Biophysical Journal. 68(1). 13–24. 66 indexed citations
17.
Schmitz, Uli, Nikolai B. Ulyanov, Anil Kumar, & Thomas Leroy James. (1993). Molecular Dynamics with Weighted Time-averaged Restraints for a DNA Octamer. Journal of Molecular Biology. 234(2). 373–389. 49 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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