Jan D. Haas

1.4k total citations
10 papers, 1.1k citations indexed

About

Jan D. Haas is a scholar working on Immunology, Dermatology and Physiology. According to data from OpenAlex, Jan D. Haas has authored 10 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Immunology, 2 papers in Dermatology and 2 papers in Physiology. Recurrent topics in Jan D. Haas's work include T-cell and B-cell Immunology (7 papers), Immune Cell Function and Interaction (7 papers) and IL-33, ST2, and ILC Pathways (2 papers). Jan D. Haas is often cited by papers focused on T-cell and B-cell Immunology (7 papers), Immune Cell Function and Interaction (7 papers) and IL-33, ST2, and ILC Pathways (2 papers). Jan D. Haas collaborates with scholars based in Germany, Chile and France. Jan D. Haas's co-authors include Immo Prinz, Reinhold Förster, Vijaykumar Chennupati, Lisa Föhse, Susanne Schmitz, Elisabeth Kremmer, Franziska Petermann, Thomas Korn, Andreas Krueger and Sarina Ravens and has published in prestigious journals such as Immunity, The Journal of Immunology and Gastroenterology.

In The Last Decade

Jan D. Haas

10 papers receiving 1.1k citations

Peers

Jan D. Haas

IMMUN

DERMA

ONCOL

MB

EPIDE

Emiliana Rodriguez Switzerland

Hideaki Sugiyama Japan

Vadim Budagian Germany

Jesse L. Gurgel United States

Vanina Lenief France

Nina Oberle Germany

Salim Bouguermouh Canada

Katarzyna Grys United Kingdom

Giampiero Girolomoni Italy

Stephanie Schulte United States

Emiliana Rodriguez Switzerland

Jan D. Haas

735 ×0.8

IMMUN

323 ×2.0

DERMA

121 ×1.1

ONCOL

233 ×2.4

MB

81 ×1.2

EPIDE

Citations per year, relative to Jan D. Haas Jan D. Haas (= 1×) peers Emiliana Rodriguez

Countries citing papers authored by Jan D. Haas

Since Specialization

Citations

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

Fields of papers citing papers by Jan D. Haas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan D. Haas. 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 Jan D. Haas. The network helps show where Jan D. Haas may publish in the future.

Co-authorship network of co-authors of Jan D. Haas

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

All Works

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10 of 10 papers shown

1.

Vandeghinste, N., Florence Marsais, Jan D. Haas, et al.. (2018). Neutralization of IL-17C Reduces Skin Inflammation in Mouse Models of Psoriasis and Atopic Dermatitis. Journal of Investigative Dermatology. 138(7). 1555–1563. 94 indexed citations

2.

Klemann, Christian, Arne Schröder, Nora Möhn, et al.. (2015). Interleukin 17, Produced by γδ T Cells, Contributes to Hepatic Inflammation in a Mouse Model of Biliary Atresia and Is Increased in Livers of Patients. Gastroenterology. 150(1). 229–241.e5. 48 indexed citations

3.

Reinhardt, Annika, Sarina Ravens, Henrike Fleige, et al.. (2014). CCR7‐mediated migration in the thymus controls γδ T‐cell development. European Journal of Immunology. 44(5). 1320–1329. 23 indexed citations

4.

Haas, Jan D., Sarina Ravens, Sandra Düber, et al.. (2012). Development of Interleukin-17-Producing γδ T Cells Is Restricted to a Functional Embryonic Wave. Immunity. 37(1). 48–59. 272 indexed citations

5.

Haas, Jan D., Kiran Nistala, Franziska Petermann, et al.. (2011). Expression of miRNAs miR-133b and miR-206 in the Il17a/f Locus Is Co-Regulated with IL-17 Production in αβ and γδ T Cells. PLoS ONE. 6(5). e20171–e20171. 50 indexed citations

6.

Föhse, Lisa, Karsten Suhre, Benjamin Wahl, et al.. (2011). High TCR diversity ensures optimal function andhomeostasis of Foxp3⁺ regulatory Tcells. European Journal of Immunology. 41(11). 3101–3113. 74 indexed citations

7.

Petermann, Franziska, Veit Rothhammer, Malte Christian Claussen, et al.. (2010). γδ T Cells Enhance Autoimmunity by Restraining Regulatory T Cell Responses via an Interleukin-23-Dependent Mechanism. Immunity. 33(3). 351–363. 228 indexed citations

8.

Malinarich, Frano, Elena Grabski, Tim Worbs, et al.. (2010). Constant TCR triggering suggests that the TCR expressed on intestinal intraepithelial γδ T cells is functional in vivo. European Journal of Immunology. 40(12). 3378–3388. 22 indexed citations

9.

Chennupati, Vijaykumar, Tim Worbs, Frano Malinarich, et al.. (2010). Intra- and Intercompartmental Movement of γδ T Cells: Intestinal Intraepithelial and Peripheral γδ T Cells Represent Exclusive Nonoverlapping Populations with Distinct Migration Characteristics. The Journal of Immunology. 185(9). 5160–5168. 69 indexed citations

10.

Haas, Jan D., Susanne Schmitz, Vijaykumar Chennupati, et al.. (2009). CCR6 and NK1.1 distinguish between IL‐17A and IFN‐γ‐producing γδ effector T cells. European Journal of Immunology. 39(12). 3488–3497. 227 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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