U. Renne

972 total citations
57 papers, 832 citations indexed

About

U. Renne is a scholar working on Genetics, Physiology and Molecular Biology. According to data from OpenAlex, U. Renne has authored 57 papers receiving a total of 832 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Genetics, 23 papers in Physiology and 14 papers in Molecular Biology. Recurrent topics in U. Renne's work include Adipose Tissue and Metabolism (22 papers), Genetic Mapping and Diversity in Plants and Animals (17 papers) and Genetic and phenotypic traits in livestock (14 papers). U. Renne is often cited by papers focused on Adipose Tissue and Metabolism (22 papers), Genetic Mapping and Diversity in Plants and Animals (17 papers) and Genetic and phenotypic traits in livestock (14 papers). U. Renne collaborates with scholars based in Germany, United Kingdom and United States. U. Renne's co-authors include L. Bünger, Gudrun A. Brockmann, Martina Langhammer, Chris Haley, M. Schwerin, G. Dietl, Sara Knott, Charlotte Rehfeldt, W. Schlote and Andreas Hoeflich and has published in prestigious journals such as PLoS ONE, Genetics and The FASEB Journal.

In The Last Decade

U. Renne

56 papers receiving 810 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
U. Renne Germany 18 404 287 236 84 79 57 832
Eugene J. Eisen United States 19 517 1.3× 222 0.8× 186 0.8× 56 0.7× 18 0.2× 28 828
O. Bellmann Germany 16 394 1.0× 158 0.6× 119 0.5× 48 0.6× 43 0.5× 29 921
M. G. Thomas United States 22 868 2.1× 88 0.3× 142 0.6× 158 1.9× 66 0.8× 46 1.4k
K. L. Hossner United States 18 229 0.6× 171 0.6× 441 1.9× 52 0.6× 137 1.7× 41 1.1k
Mark A. Fenwick United Kingdom 21 545 1.3× 70 0.2× 321 1.4× 44 0.5× 41 0.5× 26 1.7k
C. Perreau France 28 631 1.6× 70 0.2× 867 3.7× 41 0.5× 53 0.7× 72 2.3k
Woori Kwak South Korea 17 197 0.5× 122 0.4× 330 1.4× 27 0.3× 34 0.4× 51 772
Katarzyna Piórkowska Poland 17 484 1.2× 109 0.4× 354 1.5× 56 0.7× 124 1.6× 100 951
G. Pelletier Canada 21 273 0.7× 126 0.4× 205 0.9× 82 1.0× 57 0.7× 84 1.3k
M. Khalid United Kingdom 25 552 1.4× 36 0.1× 146 0.6× 60 0.7× 71 0.9× 76 1.8k

Countries citing papers authored by U. Renne

Since Specialization
Citations

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

Fields of papers citing papers by U. Renne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of U. Renne

This figure shows the co-authorship network connecting the top 25 collaborators of U. Renne. A scholar is included among the top collaborators of U. Renne 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 U. Renne. U. Renne 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.
Brenmoehl, Julia, Christina Walz, U. Renne, et al.. (2013). Metabolic Adaptations in the Liver of Born Long-Distance Running Mice. Medicine & Science in Sports & Exercise. 45(5). 841–850. 20 indexed citations
2.
3.
Lytovchenko, Oleksandr, Sebastian Hogl, Lennart Opitz, et al.. (2012). Extrinsic and intrinsic regulation of DOR/TP53INP2 expression in mice: effects of dietary fat content, tissue type and sex in adipose and muscle tissues. Nutrition & Metabolism. 9(1). 86–86. 5 indexed citations
4.
Langhammer, Martina, Maximilian Bielohuby, Peggy Stock, et al.. (2012). Phenotype Selection Reveals Coevolution of Muscle Glycogen and Protein and PTEN as a Gate Keeper for the Accretion of Muscle Mass in Adult Female Mice. PLoS ONE. 7(6). e39711–e39711. 10 indexed citations
5.
Nuernberg, Karin, Bernhard H. Breier, H Bergmann, et al.. (2011). Metabolic responses to high-fat diets rich in n-3 or n-6 long-chain polyunsaturated fatty acids in mice selected for either high body weight or leanness explain different health outcomes. Nutrition & Metabolism. 8(1). 56–56. 26 indexed citations
6.
Walther, Thomas, Martina Langhammer, Magda Kucia, et al.. (2011). High-Protein Diet in Lactation Leads to a Sudden Infant Death-Like Syndrome in Mice. PLoS ONE. 6(3). e17443–e17443. 3 indexed citations
7.
Rehfeldt, C., et al.. (2008). Overexpression of IGFBP-2 in transgenic mice affects muscle protein accretion, skeletal myofibre growth and metabolism. 16. 2 indexed citations
8.
Brockmann, Gudrun A., Ersin Karataylı, Ioannis M. Stylianou, et al.. (2007). Genetic control of lipids in the mouse cross DU6i × DBA/2. Mammalian Genome. 18(11). 757–766. 5 indexed citations
9.
Koczan, Dirk, et al.. (2007). Differentially expressed genes in adipose tissues of high body weight-selected (obese) and unselected (lean) mouse lines. Journal of Applied Genetics. 48(2). 133–143. 9 indexed citations
10.
Janczyk, Paweł, Martina Langhammer, U. Renne, V. Guiard, & W. B. Souffrant. (2006). Effect of feed supplementation with Chlorella vulgaris powder on mice reproduction.. Archiva zootechnica. 9(4). 122–134. 20 indexed citations
11.
Kuhla, S., et al.. (2004). Carbon and nitrogen content based estimation of the fat content of animal carcasses in various species. Archives of Animal Nutrition. 58(1). 37–46. 16 indexed citations
12.
Brockmann, Gudrun A., et al.. (2004). QTLs for pre- and postweaning body weight and body composition in selected mice. Mammalian Genome. 15(8). 593–609. 31 indexed citations
13.
Bünger, L., L. Varga, W. Schlote, et al.. (2004). Marker-assisted introgression of the Compact mutant myostatin allele MstnCmpt-dl1Abc into a mouse line with extreme growth effects on body composition and muscularity. Genetics Research. 84(3). 161–173. 29 indexed citations
14.
Reichart, Ursula, et al.. (2003). A Novel Leptin Receptor Variant with a Conservative Amino Acid Substitution (I359 V) in Body Weight Selected and Unselected Mouse Lines. Experimental and Clinical Endocrinology & Diabetes. 111(5). 283–287. 2 indexed citations
15.
Rehfeldt, C., et al.. (2002). Intrinsic properties of muscle satellite cells are changed in response to long-term selection of mice for different growth traits. Cell and Tissue Research. 310(3). 339–348. 18 indexed citations
16.
Lammert, A, et al.. (2002). Different isoforms of the soluble leptin receptor in non-pregnant and pregnant mice. Biochemical and Biophysical Research Communications. 298(5). 798–804. 20 indexed citations
17.
Bünger, L., et al.. (2001). Body weight limits in mice - Long term selection and single genes. Socio-Environmental Systems Modeling. 337–360. 14 indexed citations
18.
19.
Renne, U., et al.. (1996). Effects of stress-related signal molecules on cells associated with muscle tissue.. PubMed. 18(5). 383–8. 7 indexed citations
20.
Bünger, L., U. Renne, & G. Dietl. (1994). 60 generations of selection for an index combining high body weight and high stress resistance in laboratory mice.. Proceedings of the World Congress on Genetics applied to Livestock Production. 16–19. 5 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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