Ute Müh

1.9k total citations · 1 hit paper
26 papers, 1.5k citations indexed

About

Ute Müh is a scholar working on Molecular Biology, Infectious Diseases and Genetics. According to data from OpenAlex, Ute Müh has authored 26 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 10 papers in Infectious Diseases and 8 papers in Genetics. Recurrent topics in Ute Müh's work include Bacterial Genetics and Biotechnology (8 papers), Clostridium difficile and Clostridium perfringens research (6 papers) and Hepatitis C virus research (5 papers). Ute Müh is often cited by papers focused on Bacterial Genetics and Biotechnology (8 papers), Clostridium difficile and Clostridium perfringens research (6 papers) and Hepatitis C virus research (5 papers). Ute Müh collaborates with scholars based in United States, Germany and Netherlands. Ute Müh's co-authors include Brian L. Hanzelka, Eric R. Olson, Martín Schuster, Roger Heim, E. Peter Greenberg, Doug J. Bartels, Chao Lin, Yi Zhou, Ann D. Kwong and Hui‐May Chu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Gastroenterology.

In The Last Decade

Ute Müh

26 papers receiving 1.4k citations

Hit Papers

Dynamic Hepatitis C Virus Genotypic and Phenotypic Change... 2007 2026 2013 2019 2007 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ute Müh United States 16 691 576 486 415 177 26 1.5k
Shih‐Tung Liu Taiwan 22 395 0.6× 205 0.4× 219 0.5× 360 0.9× 14 0.1× 50 1.5k
Jc Cortay France 24 851 1.2× 105 0.2× 349 0.7× 134 0.3× 18 0.1× 58 1.5k
Verónica S. Martínez Australia 22 649 0.9× 123 0.2× 281 0.6× 70 0.2× 19 0.1× 40 1.4k
Keith Stephenson United Kingdom 21 795 1.2× 138 0.2× 133 0.3× 401 1.0× 10 0.1× 27 1.5k
Seyed Masoud Hosseini Iran 18 195 0.3× 130 0.2× 243 0.5× 190 0.5× 309 1.7× 114 1.5k
Yutaro Kaneko Japan 29 607 0.9× 30 0.1× 192 0.4× 306 0.7× 205 1.2× 91 2.1k
Rosa María Ribas‐Aparicio Mexico 17 382 0.6× 24 0.0× 193 0.4× 145 0.3× 106 0.6× 56 932
Santasabuj Das India 18 533 0.8× 40 0.1× 101 0.2× 139 0.3× 18 0.1× 56 1.1k
Yaomei Tian China 20 831 1.2× 14 0.0× 104 0.2× 154 0.4× 85 0.5× 36 1.5k

Countries citing papers authored by Ute Müh

Since Specialization
Citations

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

Fields of papers citing papers by Ute Müh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ute Müh

This figure shows the co-authorship network connecting the top 25 collaborators of Ute Müh. A scholar is included among the top collaborators of Ute Müh 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 Müh. Ute Müh 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.
Müh, Ute, et al.. (2025). Analysis of essential genes in Clostridioides difficile by CRISPRi and Tn-seq. Journal of Bacteriology. 207(10). e0022025–e0022025. 1 indexed citations
2.
Müh, Ute, Marcos M. Pires, Richard F. Helm, et al.. (2024). Identification of a family of peptidoglycan transpeptidases reveals that Clostridioides difficile requires noncanonical cross-links for viability. Proceedings of the National Academy of Sciences. 121(34). e2408540121–e2408540121. 7 indexed citations
3.
Müh, Ute, Craig D. Ellermeier, & David S. Weiss. (2022). The WalRK Two-Component System Is Essential for Proper Cell Envelope Biogenesis in Clostridioides difficile. Journal of Bacteriology. 204(6). e0012122–e0012122. 11 indexed citations
4.
Müh, Ute, et al.. (2020). Lysozyme Resistance in Clostridioides difficile Is Dependent on Two Peptidoglycan Deacetylases. Journal of Bacteriology. 202(22). 31 indexed citations
5.
Yahashiri, Atsushi, et al.. (2020). DrpB (YedR) Is a Nonessential Cell Division Protein in Escherichia coli. Journal of Bacteriology. 202(23). 3 indexed citations
8.
Müh, Ute, et al.. (2018). Bacterial sensing: A putative amphipathic helix in RsiV is the switch for activating σV in response to lysozyme. PLoS Genetics. 14(7). e1007527–e1007527. 14 indexed citations
9.
Wang, Tiansheng, Guy W. Bemis, Brian L. Hanzelka, et al.. (2017). Mtb PKNA/PKNB Dual Inhibition Provides Selectivity Advantages for Inhibitor Design To Minimize Host Kinase Interactions. ACS Medicinal Chemistry Letters. 8(12). 1224–1229. 40 indexed citations
10.
Jiang, Min, Nagraj Mani, Chao Lin, et al.. (2013). In Vitro Phenotypic Characterization of Hepatitis C Virus NS3 Protease Variants Observed in Clinical Studies of Telaprevir. Antimicrobial Agents and Chemotherapy. 57(12). 6236–6245. 25 indexed citations
11.
Sarrazin, Christoph, Tara L. Kieffer, Doug J. Bartels, et al.. (2007). Dynamic Hepatitis C Virus Genotypic and Phenotypic Changes in Patients Treated With the Protease Inhibitor Telaprevir. Gastroenterology. 132(5). 1767–1777. 476 indexed citations breakdown →
12.
Hanzelka, Brian L., Ute Müh, Ladislau C. Kovari, et al.. (2007). [12] TELAPREVIR (VX-950) IS A POTENT INHIBITOR OF HCV NS3 PROTEASES DERIVED FROM GENOTYPE NON-1 HCV-INFECTED PATIENTS. Journal of Hepatology. 46. S8–S8. 7 indexed citations
13.
Müh, Ute, Brian Hare, Breck A. Duerkop, et al.. (2006). A structurally unrelated mimic of a Pseudomonas aeruginosa acyl-homoserine lactone quorum-sensing signal. Proceedings of the National Academy of Sciences. 103(45). 16948–16952. 111 indexed citations
14.
Müh, Ute, Martín Schuster, Roger Heim, et al.. (2006). Novel Pseudomonas aeruginosa Quorum-Sensing Inhibitors Identified in an Ultra-High-Throughput Screen. Antimicrobial Agents and Chemotherapy. 50(11). 3674–3679. 217 indexed citations
15.
Yuan, Wei, Yong Jia, Kristi D. Snell, et al.. (2001). Class I and III Polyhydroxyalkanoate Synthases from Ralstonia eutropha and Allochromatium vinosum: Characterization and Substrate Specificity Studies. Archives of Biochemistry and Biophysics. 394(1). 87–98. 117 indexed citations
16.
Müh, Ute, Wolfgang Buckel, & Eckhard Bill. (1997). Mössbauer Study of 4‐Hydroxybutyryl‐CoA Dehydratase Probing the Role of an Iron‐Sulfur Cluster in an Overall Non‐Redox Reaction. European Journal of Biochemistry. 248(2). 380–384. 17 indexed citations
18.
Müh, Ute, Vincent Massey, & Charles H. Williams. (1994). Lactate monooxygenase. I. Expression of the mycobacterial gene in Escherichia coli and site-directed mutagenesis of lysine 266.. Journal of Biological Chemistry. 269(11). 7982–7988. 25 indexed citations
19.
Müh, Ute, Charles H. Williams, & Vincent Massey. (1994). Lactate monooxygenase. II. Site-directed mutagenesis of the postulated active site base histidine 290.. Journal of Biological Chemistry. 269(11). 7989–7993. 26 indexed citations
20.
Müh, Ute. (1993). Lactate oxidase: Expression of the gene in Escherichia coli and studies of the reaction mechanism through active site mutations.. Deep Blue (University of Michigan). 1 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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