Ewa Wladykowski

1.1k total citations
18 papers, 841 citations indexed

About

Ewa Wladykowski is a scholar working on Molecular Biology, Neurology and Dermatology. According to data from OpenAlex, Ewa Wladykowski has authored 18 papers receiving a total of 841 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Neurology and 6 papers in Dermatology. Recurrent topics in Ewa Wladykowski's work include Barrier Structure and Function Studies (8 papers), Dermatology and Skin Diseases (5 papers) and Connexins and lens biology (5 papers). Ewa Wladykowski is often cited by papers focused on Barrier Structure and Function Studies (8 papers), Dermatology and Skin Diseases (5 papers) and Connexins and lens biology (5 papers). Ewa Wladykowski collaborates with scholars based in Germany, Austria and Netherlands. Ewa Wladykowski's co-authors include Ingrid Moll, Johanna M. Brandner, Pia Houdek, S Kief, Martin J. Behne, Nina Kirschner, Sabine Vidal‐y‐Sy, J. M. Brandner, Pavel Houdek and Peter Von Den Driesch and has published in prestigious journals such as PLoS ONE, Cancer Research and Scientific Reports.

In The Last Decade

Ewa Wladykowski

18 papers receiving 826 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ewa Wladykowski Germany 14 385 271 209 154 139 18 841
Nina Kirschner Germany 10 348 0.9× 292 1.1× 277 1.3× 110 0.7× 147 1.1× 10 796
Pia Houdek Germany 17 377 1.0× 412 1.5× 247 1.2× 129 0.8× 164 1.2× 19 1.2k
Mariko Yokouchi Japan 10 486 1.3× 165 0.6× 141 0.7× 250 1.6× 157 1.1× 12 965
Patrick A.M. Jansen Netherlands 16 270 0.7× 357 1.3× 154 0.7× 81 0.5× 27 0.2× 33 904
Michael Schunck Germany 13 628 1.6× 264 1.0× 13 0.1× 172 1.1× 150 1.1× 24 1.1k
Chanisa Kiatsurayanon Japan 15 436 1.1× 186 0.7× 34 0.2× 216 1.4× 45 0.3× 20 825
Petra Ovaere Belgium 5 304 0.8× 345 1.3× 10 0.0× 118 0.8× 82 0.6× 6 796
Hanna Niehues Netherlands 10 294 0.8× 214 0.8× 8 0.0× 92 0.6× 78 0.6× 27 665
Caterina Barresi Austria 13 306 0.8× 268 1.0× 8 0.0× 106 0.7× 49 0.4× 16 841
Bruno Méhul France 18 301 0.8× 621 2.3× 19 0.1× 50 0.3× 53 0.4× 27 1.3k

Countries citing papers authored by Ewa Wladykowski

Since Specialization
Citations

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

Fields of papers citing papers by Ewa Wladykowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ewa Wladykowski

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

All Works

18 of 18 papers shown
1.
Pantel, Klaus, Stefan W. Schneider, Jochen Utikal, et al.. (2024). Evaluation of S100A8/A9 and neutrophils as prognostic markers in metastatic melanoma patients under immune-checkpoint inhibition. Translational Oncology. 52. 102224–102224. 1 indexed citations
2.
John, Axel, Sabine Vidal‐y‐Sy, Pia Houdek, et al.. (2020). Urothelial Carcinoma of the Bladder Induces Endothelial Cell Activation and Hypercoagulation. Molecular Cancer Research. 18(7). 1099–1109. 23 indexed citations
3.
Vidal‐y‐Sy, Sabine, Marek Haftek, Ewa Wladykowski, et al.. (2020). Claudin-1 decrease impacts epidermal barrier function in atopic dermatitis lesions dose-dependently. Scientific Reports. 10(1). 2024–2024. 93 indexed citations
4.
Zorn‐Kruppa, Michaela, Sabine Vidal‐y‐Sy, Pia Houdek, et al.. (2018). Tight Junction barriers in human hair follicles – role of claudin-1. Scientific Reports. 8(1). 49 indexed citations
5.
Bäsler, Katja, M. Galliano, Holger Rohde, et al.. (2017). Biphasic influence of Staphylococcus aureus on human epidermal tight junctions. Annals of the New York Academy of Sciences. 1405(1). 53–70. 33 indexed citations
6.
Niehues, Hanna, Diana Rodijk‐Olthuis, Joost Schalkwijk, et al.. (2016). 077 Epidermal equivalents of filaggrin null keratinocytes do not show impaired skin barrier function. Journal of Investigative Dermatology. 136(9). S174–S174. 6 indexed citations
7.
Gruber, Robert, Christian Börnchen, Anne Daubmann, et al.. (2015). Diverse Regulation of Claudin-1 and Claudin-4 in Atopic Dermatitis. American Journal Of Pathology. 185(10). 2777–2789. 117 indexed citations
8.
Houdek, Pia, Michaela Zorn‐Kruppa, Ewa Wladykowski, et al.. (2015). A custom tailored model to investigate skin penetration in porcine skin and its comparison with human skin. European Journal of Pharmaceutics and Biopharmaceutics. 95(Pt A). 99–109. 42 indexed citations
9.
Zorn‐Kruppa, Michaela, Pia Houdek, Ewa Wladykowski, et al.. (2014). Determining the Depth of Injury in Bioengineered Tissue Models of Cornea and Conjunctiva for the Prediction of All Three Ocular GHS Categories. PLoS ONE. 9(12). e114181–e114181. 10 indexed citations
10.
Tilling, Thomas, Ewa Wladykowski, Antonio Virgilio Failla, et al.. (2013). Immunohistochemical analyses point to epidermal origin of human Merkel cells. Histochemistry and Cell Biology. 141(4). 407–421. 28 indexed citations
11.
Haass, Nikolas K., Ewa Wladykowski, Phyllis A. Gimotty, et al.. (2009). Melanoma progression exhibits a significant impact on connexin expression patterns in the epidermal tumor microenvironment. Histochemistry and Cell Biology. 133(1). 113–124. 35 indexed citations
12.
Brandner, J. M., et al.. (2009). Evidence for distinct populations of human Merkel cells. Histochemistry and Cell Biology. 132(1). 83–93. 38 indexed citations
13.
Kirschner, Nina, Peter Von Den Driesch, Ewa Wladykowski, et al.. (2009). Alteration of Tight Junction Proteins Is an Early Event in Psoriasis. American Journal Of Pathology. 175(3). 1095–1106. 124 indexed citations
14.
Ohnemus, Ulrich, Pia Houdek, Holger Rohde, et al.. (2007). Regulation of Epidermal Tight-Junctions (TJ) during Infection with Exfoliative Toxin-Negative Staphylococcus Strains. Journal of Investigative Dermatology. 128(4). 906–916. 95 indexed citations
15.
Brandner, J. M., S Kief, Ewa Wladykowski, Pavel Houdek, & Ingrid Moll. (2006). Tight Junction Proteins in the Skin. Skin Pharmacology and Physiology. 19(2). 71–77. 68 indexed citations
16.
Haass, Nikolas K., Ewa Wladykowski, S Kief, Ingrid Moll, & Johanna M. Brandner. (2005). Differential Induction of Connexins 26 and 30 in Skin Tumors and Their Adjacent Epidermis. Journal of Histochemistry & Cytochemistry. 54(2). 171–182. 30 indexed citations
17.
Haass, Nikolas K., Johanna M. Brandner, Patricia Brafford, et al.. (2004). Differential expression of connexins in melanoma and adjacent epidermis. Cancer Research. 64. 639–639. 1 indexed citations
18.
Brandner, Johanna M., et al.. (2003). Expression and localization of tight junction-associated proteins in human hair follicles. Archives of Dermatological Research. 295(5). 211–221. 48 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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