Anne Uv

2.3k total citations
28 papers, 1.5k citations indexed

About

Anne Uv is a scholar working on Molecular Biology, Immunology and Cell Biology. According to data from OpenAlex, Anne Uv has authored 28 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 14 papers in Immunology and 7 papers in Cell Biology. Recurrent topics in Anne Uv's work include Invertebrate Immune Response Mechanisms (13 papers), Neurobiology and Insect Physiology Research (6 papers) and RNA Research and Splicing (5 papers). Anne Uv is often cited by papers focused on Invertebrate Immune Response Mechanisms (13 papers), Neurobiology and Insect Physiology Research (6 papers) and RNA Research and Splicing (5 papers). Anne Uv collaborates with scholars based in Sweden, Germany and United Kingdom. Anne Uv's co-authors include Sarah J. Bray, Christos Samakovlis, Bernard Moussian, Johanna Hemphälä, Heinz Schwarz, Rafael Cantera, Sigrun Helms, Christer Betsholtz, Ulf Nannmark and Richard A. Lang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Genes & Development and The Journal of Cell Biology.

In The Last Decade

Anne Uv

28 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anne Uv Sweden	20	998	475	359	329	155	28	1.5k
Stefan Luschnig Germany	23	1.4k 1.4×	458 1.0×	483 1.3×	636 1.9×	34 0.2×	43	2.0k
Nicholas S. Sokol United States	22	1.3k 1.3×	250 0.5×	426 1.2×	190 0.6×	46 0.3×	37	2.0k
Alicia Hidalgo United Kingdom	25	1.5k 1.5×	352 0.7×	1.1k 3.1×	391 1.2×	73 0.5×	60	2.4k
Thomas Osterwalder Switzerland	14	840 0.8×	169 0.4×	738 2.1×	376 1.1×	91 0.6×	14	1.7k
Angela Giangrande France	28	1.8k 1.8×	498 1.0×	1.1k 2.9×	534 1.6×	54 0.3×	93	2.5k
Alexander J. Osborn United States	16	1.5k 1.5×	289 0.6×	752 2.1×	506 1.5×	31 0.2×	24	2.5k
Marta Llimargas Spain	18	754 0.8×	257 0.5×	258 0.7×	378 1.1×	25 0.2×	34	1000
Katarína Tiklová Sweden	14	753 0.8×	201 0.4×	395 1.1×	162 0.5×	102 0.7×	20	1.1k
Johanna Hemphälä Sweden	8	608 0.6×	246 0.5×	264 0.7×	262 0.8×	19 0.1×	8	821
Joachim Urban Germany	18	1.6k 1.6×	362 0.8×	1.4k 3.9×	525 1.6×	42 0.3×	24	2.3k

Countries citing papers authored by Anne Uv

Since Specialization

Citations

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

Fields of papers citing papers by Anne Uv

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anne Uv

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

All Works

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20 of 20 papers shown

Wolfstetter, Georg, Kathrin Pfeifer, Mattias Backman, et al.. (2020). Identification of the Wallenda JNKKK as an Alk suppressor reveals increased competitiveness of Alk-expressing cells. Scientific Reports. 10(1). 14954–14954. 4 indexed citations

Cinege, Gyöngyi, János Zsámboki, Anne Uv, et al.. (2017). Genes encoding cuticular proteins are components of the Nimrod gene cluster in Drosophila. Insect Biochemistry and Molecular Biology. 87. 45–54. 13 indexed citations

Ejeskär, Katarina, et al.. (2015). The Unique Non-Catalytic C-Terminus of P37delta-PI3K Adds Proliferative Properties In Vitro and In Vivo. PLoS ONE. 10(5). e0127497–e0127497. 2 indexed citations

Syed, Zulfeqhar A., Jimit Shah, Tinri Aegerter‐Wilmsen, et al.. (2015). The Triple-Repeat Protein Anakonda Controls Epithelial Tricellular Junction Formation in Drosophila. Developmental Cell. 33(5). 535–548. 62 indexed citations

Luschnig, Stefan & Anne Uv. (2013). Luminal matrices: An inside view on organ morphogenesis. Experimental Cell Research. 321(1). 64–70. 37 indexed citations

Syed, Zulfeqhar A., et al.. (2012). A Luminal Glycoprotein Drives Dose-Dependent Diameter Expansion of the Drosophila melanogaster Hindgut Tube. PLoS Genetics. 8(8). e1002850–e1002850. 26 indexed citations

Gerhardt, Holger, et al.. (2011). A Two-Way Communication between Microglial Cells and Angiogenic Sprouts Regulates Angiogenesis in Aortic Ring Cultures. PLoS ONE. 6(1). e15846–e15846. 182 indexed citations

Fransson, Susanne, Anne Uv, Helena Eriksson, et al.. (2011). p37δ is a new isoform of PI3K p110δ that increases cell proliferation and is overexpressed in tumors. Oncogene. 31(27). 3277–3286. 19 indexed citations

Schwarz, Heinz, et al.. (2010). Trafficking through COPII Stabilises Cell Polarity and Drives Secretion during Drosophila Epidermal Differentiation. PLoS ONE. 5(5). e10802–e10802. 44 indexed citations

10.

Moussian, Bernard, et al.. (2010). Tissue-autonomous EcR functions are required for concurrent organ morphogenesis in the Drosophila embryo. Mechanisms of Development. 127(5-6). 308–319. 24 indexed citations

11.

Uv, Anne & Bernard Moussian. (2009). The apical plasma membrane of Drosophila embryonic epithelia. European Journal of Cell Biology. 89(2-3). 208–211. 14 indexed citations

12.

Syed, Zulfeqhar A., et al.. (2008). A Potential Role for Drosophila Mucins in Development and Physiology. PLoS ONE. 3(8). e3041–e3041. 80 indexed citations

13.

Helms, Sigrun, et al.. (2005). Hormonal regulation of mummy is needed for apical extracellular matrix formation and epithelial morphogenesis in Drosophila. Development. 133(2). 331–341. 65 indexed citations

14.

Hemphälä, Johanna, et al.. (2005). A Transient Luminal Chitinous Matrix Is Required to Model Epithelial Tube Diameter in the Drosophila Trachea. Developmental Cell. 9(3). 423–430. 141 indexed citations

15.

Moussian, Bernard & Anne Uv. (2005). An ancient control of epithelial barrier formation and wound healing. BioEssays. 27(10). 987–990. 24 indexed citations

16.

Uv, Anne. (2003). Drosophila tracheal morphogenesis: intricate cellular solutions to basic plumbing problems. Trends in Cell Biology. 13(6). 301–309. 102 indexed citations

17.

Uv, Anne, et al.. (2000). members only encodes a Drosophila nucleoporin required for rel protein import and immune response activation.. PubMed. 14(15). 1945–57. 1 indexed citations

18.

Uv, Anne, et al.. (1997). Tissue-Specific Splicing and Functions of the Drosophila Transcription Factor Grainyhead. Molecular and Cellular Biology. 17(11). 6727–6735. 70 indexed citations

19.

Uv, Anne, Christopher R. L. Thompson, & Sarah J. Bray. (1994). The Drosophila Tissue-Specific Factor Grainyhead Contains Novel DNA-Binding and Dimerization Domains Which Are Conserved in the Human Protein CP2. Molecular and Cellular Biology. 14(6). 4020–4031. 16 indexed citations

20.

Uv, Anne, Christopher R. L. Thompson, & Sarah J. Bray. (1994). The Drosophila tissue-specific factor Grainyhead contains novel DNA-binding and dimerization domains which are conserved in the human protein CP2.. Molecular and Cellular Biology. 14(6). 4020–4031. 66 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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