Anna Dittrich

789 total citations
25 papers, 567 citations indexed

About

Anna Dittrich is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Anna Dittrich has authored 25 papers receiving a total of 567 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 15 papers in Oncology and 8 papers in Immunology. Recurrent topics in Anna Dittrich's work include Cytokine Signaling Pathways and Interactions (15 papers), Gene Regulatory Network Analysis (4 papers) and Protein Tyrosine Phosphatases (4 papers). Anna Dittrich is often cited by papers focused on Cytokine Signaling Pathways and Interactions (15 papers), Gene Regulatory Network Analysis (4 papers) and Protein Tyrosine Phosphatases (4 papers). Anna Dittrich collaborates with scholars based in Germany, United States and Belgium. Anna Dittrich's co-authors include Fred Schaper, Christina Khouri, Alexandra Wolf, Pia Müller, Heinrich J. Huber, Martin Mönnigmann, Tom Quaiser, Stefan Streif, Eric Bullinger and Rolf Findeisen and has published in prestigious journals such as Hepatology, Frontiers in Immunology and Frontiers in Microbiology.

In The Last Decade

Anna Dittrich

25 papers receiving 556 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anna Dittrich Germany 11 212 202 182 57 42 25 567
Christopher C. Wolford United States 6 289 1.4× 125 0.6× 174 1.0× 75 1.3× 47 1.1× 7 597
Aurelia Walczak‐Drzewiecka Poland 17 256 1.2× 253 1.3× 84 0.5× 71 1.2× 67 1.6× 31 625
Neele Schumacher Germany 14 193 0.9× 259 1.3× 253 1.4× 66 1.2× 76 1.8× 17 607
Anastasia Meshcheryakova Austria 15 381 1.8× 228 1.1× 206 1.1× 105 1.8× 66 1.6× 30 771
B. Blanchard France 8 222 1.0× 200 1.0× 108 0.6× 33 0.6× 50 1.2× 8 547
Hideyuki Higashi United States 12 287 1.4× 121 0.6× 147 0.8× 99 1.7× 28 0.7× 24 693
Gillian M. Tannahill United Kingdom 12 335 1.6× 319 1.6× 152 0.8× 66 1.2× 56 1.3× 15 720
Yoshiyasu Esaki Japan 4 120 0.6× 229 1.1× 98 0.5× 72 1.3× 64 1.5× 6 569
Shuji Matsuoka Japan 12 199 0.9× 254 1.3× 74 0.4× 35 0.6× 87 2.1× 21 585
Anna Jia China 15 251 1.2× 358 1.8× 141 0.8× 100 1.8× 72 1.7× 19 666

Countries citing papers authored by Anna Dittrich

Since Specialization
Citations

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

Fields of papers citing papers by Anna Dittrich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Dittrich

This figure shows the co-authorship network connecting the top 25 collaborators of Anna Dittrich. A scholar is included among the top collaborators of Anna Dittrich 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 Anna Dittrich. Anna Dittrich 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.
Lokau, Juliane, Yvonne Garbers, Manuel M. Vicente, et al.. (2025). Long-term increase in soluble interleukin-6 receptor levels in convalescents after mild COVID-19 infection. Frontiers in Immunology. 15. 1488745–1488745. 4 indexed citations
2.
Heyer, Robert, Anna Dittrich, Daniel Wibberg, et al.. (2024). Tracing active members in microbial communities by BONCAT and click chemistry-based enrichment of newly synthesized proteins. ISME Communications. 4(1). ycae153–ycae153. 1 indexed citations
3.
Naß, Norbert, et al.. (2024). Dysregulated Gab1 signalling in triple negative breast cancer. Cell Communication and Signaling. 22(1). 161–161. 1 indexed citations
4.
Dittrich, Anna, et al.. (2024). Detection, isolation and characterization of phage-host complexes using BONCAT and click chemistry. Frontiers in Microbiology. 15. 1434301–1434301. 3 indexed citations
5.
Dittrich, Anna, et al.. (2023). Quantification of total and phosphorylated STAT3 by calibrated western blotting. STAR Protocols. 4(3). 102508–102508. 2 indexed citations
6.
Dittrich, Anna, et al.. (2023). Quantification of membrane-bound cytokine receptors by calibrated flow cytometry. STAR Protocols. 4(3). 102511–102511. 2 indexed citations
7.
Schulz, S., et al.. (2022). Non‐canonical STAT3 function reduces REDD1 transcription. FEBS Journal. 290(7). 1765–1781. 5 indexed citations
8.
Komorowski, Michał, et al.. (2021). The tyrosine phosphatase SHP2 increases robustness and information transfer within IL-6-induced JAK/STAT signalling. Cell Communication and Signaling. 19(1). 94–94. 35 indexed citations
9.
Komorowski, Michał, et al.. (2019). Robustness and Information Transfer within IL-6-induced JAK/STAT Signalling. Communications Biology. 2(1). 27–27. 43 indexed citations
10.
Kaempfer, Raymond, et al.. (2019). Intragenic regulation of SOCS3 isoforms. Cell Communication and Signaling. 17(1). 70–70. 9 indexed citations
11.
Streif, Stefan, Eric Bullinger, Rolf Findeisen, et al.. (2019). Response to IL-6 trans- and IL-6 classic signalling is determined by the ratio of the IL-6 receptor α to gp130 expression: fusing experimental insights and dynamic modelling. Cell Communication and Signaling. 17(1). 46–46. 112 indexed citations
12.
Haver, Delphi Van, Kris Gevaert, Francis Impens, et al.. (2018). Quantitative proteomics and systems analysis of cultured H9C2 cardiomyoblasts during differentiation over time supports a ‘function follows form’ model of differentiation. Molecular Omics. 14(3). 181–196. 12 indexed citations
13.
Poli, Valeria, et al.. (2016). Interleukin-6 influences stress-signalling by reducing the expression of the mTOR-inhibitor REDD1 in a STAT3-dependent manner. Cellular Signalling. 28(8). 907–916. 39 indexed citations
14.
Dittrich, Anna, et al.. (2015). Systems biology of IL-6, IL-12 family cytokines. Cytokine & Growth Factor Reviews. 26(5). 595–602. 35 indexed citations
15.
16.
Dittrich, Anna, Tom Quaiser, Christina Khouri, et al.. (2012). Model-driven experimental analysis of the function of SHP-2 in IL-6-induced Jak/STAT signaling. Molecular BioSystems. 8(8). 2119–2134. 28 indexed citations
17.
Dittrich, Anna, Elmar Siewert, & Fred Schaper. (2012). Determination of Protein Turnover Rates in the JAK/STAT Pathway Using a Radioactive Pulse-Chase Approach. Methods in molecular biology. 967. 69–80. 3 indexed citations
18.
Dittrich, Anna, Christina Khouri, Sara Dutton Sackett, et al.. (2011). Glucocorticoids Increase Interleukin–6–Dependent Gene Induction by Interfering With the Expression of the Suppressor of Cytokine Signaling 3 Feedback Inhibitor. Hepatology. 55(1). 256–266. 36 indexed citations
19.
Dittrich, Anna, et al.. (2011). Interleukin-6 signalling: More than Jaks and STATs. European Journal of Cell Biology. 91(6-7). 486–495. 136 indexed citations
20.
Quaiser, Tom, Anna Dittrich, Fred Schaper, & Martin Mönnigmann. (2011). A simple work flow for biologically inspired model reduction - application to early JAK-STAT signaling. BMC Systems Biology. 5(1). 30–30. 26 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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