Ute Dreses‐Werringloer

34 total papers · 2.0k total citations
22 papers, 1.2k citations indexed

About

Ute Dreses‐Werringloer is a scholar working on Microbiology, Molecular Biology and Epidemiology. According to data from OpenAlex, Ute Dreses‐Werringloer has authored 22 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Microbiology, 9 papers in Molecular Biology and 8 papers in Epidemiology. Recurrent topics in Ute Dreses‐Werringloer's work include Reproductive tract infections research (9 papers), Alzheimer's disease research and treatments (7 papers) and Urinary Tract Infections Management (6 papers). Ute Dreses‐Werringloer is often cited by papers focused on Reproductive tract infections research (9 papers), Alzheimer's disease research and treatments (7 papers) and Urinary Tract Infections Management (6 papers). Ute Dreses‐Werringloer collaborates with scholars based in United States, Germany and Australia. Ute Dreses‐Werringloer's co-authors include Philippe Marambaud, Valérie Vingtdeux, Haitian Zhao, Alan P. Hudson, H. Zeidler, Peter Davies, Peter J. Davies, Lars Köhler, Judith A. Whittum‐Hudson and Concepcion Conejero‐Goldberg and has published in prestigious journals such as Cell, PLoS ONE and American Journal of Psychiatry.

In The Last Decade

Ute Dreses‐Werringloer

21 papers receiving 1.2k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ute Dreses‐Werringloer 413 345 272 214 150 22 1.2k
Ishan Patro 369 0.9× 230 0.7× 59 0.2× 105 0.5× 250 1.7× 57 1.5k
Thomas Birchler 306 0.7× 428 1.2× 103 0.4× 87 0.4× 71 0.5× 16 1.5k
R. Bryan Rock 341 0.8× 196 0.6× 217 0.8× 249 1.2× 229 1.5× 21 1.8k
Shufang Xia 535 1.3× 424 1.2× 103 0.4× 177 0.8× 52 0.3× 34 1.2k
Fabio Cafini 514 1.2× 320 0.9× 75 0.3× 267 1.2× 369 2.5× 41 1.8k
Qiqi Song 546 1.3× 128 0.4× 67 0.2× 184 0.9× 120 0.8× 41 1.6k
Jinchao Hou 415 1.0× 127 0.4× 105 0.4× 200 0.9× 37 0.2× 35 1.1k
Wen Wu 302 0.7× 247 0.7× 43 0.2× 148 0.7× 55 0.4× 60 1.4k
Min-Seon Kim 831 2.0× 612 1.8× 58 0.2× 317 1.5× 45 0.3× 11 1.8k
Shea J. Andrews 881 2.1× 560 1.6× 28 0.1× 105 0.5× 112 0.7× 47 1.9k

Countries citing papers authored by Ute Dreses‐Werringloer

Since Specialization
Citations

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

Fields of papers citing papers by Ute Dreses‐Werringloer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ute Dreses‐Werringloer

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

All Works

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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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