Anja Sieber

2.4k total citations · 1 hit paper
19 papers, 1.2k citations indexed

About

Anja Sieber is a scholar working on Molecular Biology, Computational Theory and Mathematics and Biophysics. According to data from OpenAlex, Anja Sieber has authored 19 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 4 papers in Biophysics. Recurrent topics in Anja Sieber's work include Gene Regulatory Network Analysis (5 papers), Melanoma and MAPK Pathways (5 papers) and Computational Drug Discovery Methods (4 papers). Anja Sieber is often cited by papers focused on Gene Regulatory Network Analysis (5 papers), Melanoma and MAPK Pathways (5 papers) and Computational Drug Discovery Methods (4 papers). Anja Sieber collaborates with scholars based in Germany, United Kingdom and Netherlands. Anja Sieber's co-authors include Nils Blüthgen, Bertram Klinger, Julio Sáez-Rodríguez, Mathew J. Garnett, Florian Uhlitz, Michaël Schubert, Sascha Sauer, Martina Klünemann, Raphaela Fritsche‐Guenther and Franziska Witzel and has published in prestigious journals such as Nature Communications, Bioinformatics and The Journal of Immunology.

In The Last Decade

Anja Sieber

18 papers receiving 1.1k citations

Hit Papers

Perturbation-response genes reveal signaling footprints i... 2017 2026 2020 2023 2017 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anja Sieber Germany 12 775 227 195 185 111 19 1.2k
Luz García‐Alonso United Kingdom 15 1.1k 1.5× 156 0.7× 164 0.8× 215 1.2× 161 1.5× 23 1.5k
Bertram Klinger Germany 15 764 1.0× 295 1.3× 173 0.9× 227 1.2× 51 0.5× 29 1.1k
Christian H. Holland Germany 9 802 1.0× 145 0.6× 304 1.6× 164 0.9× 62 0.6× 14 1.3k
Michaël Schubert Netherlands 9 683 0.9× 200 0.9× 263 1.3× 189 1.0× 90 0.8× 14 1.0k
Fabian Coscia Germany 17 1.1k 1.4× 332 1.5× 184 0.9× 266 1.4× 59 0.5× 29 1.7k
David Twomey United States 5 1.1k 1.4× 418 1.8× 195 1.0× 242 1.3× 58 0.5× 7 1.6k
Andrew L. Ji United States 8 986 1.3× 275 1.2× 282 1.4× 250 1.4× 63 0.6× 15 1.3k
Daniel C. Kirouac United States 16 684 0.9× 270 1.2× 166 0.9× 64 0.3× 51 0.5× 28 1.2k
Darren R. Tyson United States 25 1.0k 1.3× 546 2.4× 110 0.6× 360 1.9× 85 0.8× 55 1.7k
Sriganesh Srihari Australia 21 941 1.2× 396 1.7× 135 0.7× 309 1.7× 91 0.8× 40 1.4k

Countries citing papers authored by Anja Sieber

Since Specialization
Citations

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

Fields of papers citing papers by Anja Sieber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anja Sieber

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

All Works

19 of 19 papers shown
1.
Klinger, Bertram, Anja Sieber, Henrik Zauber, et al.. (2025). Spike-in enhanced phosphoproteomics uncovers synergistic signaling responses to MEK inhibition in colon cancer cells. Nature Communications. 16(1). 4884–4884. 1 indexed citations
2.
Astaburuaga-García, Rosario, et al.. (2024). RUCova: Removal of Unwanted Covariance in mass cytometry data. Bioinformatics. 40(11).
3.
Klinger, Bertram, et al.. (2023). Modeling unveils sex differences of signaling networks in mouse embryonic stem cells. Molecular Systems Biology. 19(11). e11510–e11510. 1 indexed citations
4.
Bosdriesz, Evert, et al.. (2022). Identifying mutant-specific multi-drug combinations using comparative network reconstruction. iScience. 25(8). 104760–104760. 2 indexed citations
5.
Schoetz, Ulrike, Diana Klein, Julia Heß, et al.. (2021). Early senescence and production of senescence-associated cytokines are major determinants of radioresistance in head-and-neck squamous cell carcinoma. Cell Death and Disease. 12(12). 1162–1162. 46 indexed citations
6.
Klinger, Bertram, Tommaso Mari, Joern Toedling, et al.. (2021). Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance. PLoS Computational Biology. 17(11). e1009515–e1009515. 5 indexed citations
7.
Kuhn, Natalia, Bertram Klinger, Florian Uhlitz, et al.. (2020). Mutation-specific effects of NRAS oncogenes in colorectal cancer cells. Advances in Biological Regulation. 79. 100778–100778. 6 indexed citations
8.
Hood, Fiona E., Bertram Klinger, Anna U. Newlaczyl, et al.. (2019). Isoform-specific Ras signaling is growth factor dependent. Molecular Biology of the Cell. 30(9). 1108–1117. 22 indexed citations
9.
Bosdriesz, Evert, Anirudh Prahallad, Bertram Klinger, et al.. (2018). Comparative Network Reconstruction using mixed integer programming. Bioinformatics. 34(17). i997–i1004. 6 indexed citations
10.
Klinger, Bertram, Torsten Groß, Anja Sieber, et al.. (2018). Modelling signalling networks from perturbation data. Bioinformatics. 34(23). 4079–4086. 14 indexed citations
11.
Eduati, Federica, Bertram Klinger, Thomas Cokelaer, et al.. (2017). Drug Resistance Mechanisms in Colorectal Cancer Dissected with Cell Type–Specific Dynamic Logic Models. Cancer Research. 77(12). 3364–3375. 73 indexed citations
12.
Schubert, Michaël, Bertram Klinger, Martina Klünemann, et al.. (2017). Perturbation-response genes reveal signaling footprints in cancer gene expression. Nature Communications. 9(1). 20–20. 444 indexed citations breakdown →
13.
Uhlitz, Florian, Anja Sieber, Emanuel Wyler, et al.. (2017). An immediate–late gene expression module decodes ERK signal duration. Molecular Systems Biology. 13(5). 928–928. 41 indexed citations
14.
Witzel, Franziska, et al.. (2015). Analysis of impedance-based cellular growth assays. Bioinformatics. 31(16). 2705–2712. 31 indexed citations
15.
Schulz, Edda G., Johannes Meisig, Tomonori Nakamura, et al.. (2014). The Two Active X Chromosomes in Female ESCs Block Exit from the Pluripotent State by Modulating the ESC Signaling Network. Cell stem cell. 14(2). 203–216. 129 indexed citations
16.
Klinger, Bertram, Anja Sieber, Raphaela Fritsche‐Guenther, et al.. (2013). Network quantification of EGFR signaling unveils potential for targeted combination therapy. Molecular Systems Biology. 9(1). 673–673. 119 indexed citations
17.
Fritsche‐Guenther, Raphaela, Franziska Witzel, Anja Sieber, et al.. (2011). Strong negative feedback from Erk to Raf confers robustness to MAPK signalling. Molecular Systems Biology. 7(1). 489–489. 148 indexed citations
18.
Zwirner, Jörg, Otto Götze, Anja Sieber, et al.. (1997). Blood‐ and skin‐derived monocytes/macrophages respond to C3a but not to C3a(desArg) with a transient release of calcium via a pertussis toxin‐sensitive signal transduction pathway. European Journal of Immunology. 27(9). 2317–2322. 35 indexed citations
19.
Werfel, Thomas, Jörg Zwirner, Marc Oppermann, et al.. (1996). CD88 antibodies specifically bind to C5aR on dermal CD117+ and CD14+ cells and react with a desmosomal antigen in human skin. The Journal of Immunology. 157(4). 1729–1735. 29 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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