Sophia Müller‐Dott

1.8k total citations · 2 hit papers
9 papers, 625 citations indexed

About

Sophia Müller‐Dott is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, Sophia Müller‐Dott has authored 9 papers receiving a total of 625 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 1 paper in Oncology. Recurrent topics in Sophia Müller‐Dott's work include Bioinformatics and Genomic Networks (6 papers), Single-cell and spatial transcriptomics (3 papers) and Gene Regulatory Network Analysis (3 papers). Sophia Müller‐Dott is often cited by papers focused on Bioinformatics and Genomic Networks (6 papers), Single-cell and spatial transcriptomics (3 papers) and Gene Regulatory Network Analysis (3 papers). Sophia Müller‐Dott collaborates with scholars based in Germany, United Kingdom and United States. Sophia Müller‐Dott's co-authors include Julio Sáez-Rodríguez, Ricardo O. Ramirez Flores, Pau Badia-i-Mompel, Aurélien Dugourd, Petr Tauš, Christian H. Holland, Celina Geiß, Daniel Dimitrov, Jana M. Braunger and Rémi Trimbour and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Sophia Müller‐Dott

8 papers receiving 623 citations

Hit Papers

decoupleR: ensemble of co... 2022 2026 2023 2024 2022 2023 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sophia Müller‐Dott Germany 6 402 126 72 66 46 9 625
Pau Badia-i-Mompel Germany 6 442 1.1× 136 1.1× 76 1.1× 69 1.0× 46 1.0× 9 695
Zhuoqing Fang United States 10 396 1.0× 102 0.8× 73 1.0× 87 1.3× 49 1.1× 24 657
Cameron G. Williams Australia 3 322 0.8× 119 0.9× 80 1.1× 64 1.0× 23 0.5× 5 466
Jayson Harshbarger Japan 5 501 1.2× 154 1.2× 112 1.6× 105 1.6× 41 0.9× 6 661
Daniel Dimitrov Germany 7 405 1.0× 177 1.4× 77 1.1× 93 1.4× 21 0.5× 13 675
Anne Senabouth Australia 13 459 1.1× 120 1.0× 99 1.4× 44 0.7× 102 2.2× 15 603
Evelina Sjöstedt Sweden 10 281 0.7× 66 0.5× 74 1.0× 98 1.5× 36 0.8× 20 517
Mahmoud M. Ibrahim Germany 11 646 1.6× 147 1.2× 133 1.8× 90 1.4× 68 1.5× 13 864
Takahiro Asatsuma Australia 1 310 0.8× 88 0.7× 79 1.1× 54 0.8× 21 0.5× 2 418
Vince Carey United States 3 397 1.0× 101 0.8× 104 1.4× 42 0.6× 31 0.7× 4 512

Countries citing papers authored by Sophia Müller‐Dott

Since Specialization
Citations

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

Fields of papers citing papers by Sophia Müller‐Dott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sophia Müller‐Dott. 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 Sophia Müller‐Dott. The network helps show where Sophia Müller‐Dott may publish in the future.

Co-authorship network of co-authors of Sophia Müller‐Dott

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

All Works

9 of 9 papers shown
1.
Müller‐Dott, Sophia, Eric J. Jaehnig, Wen Jiang, et al.. (2025). Comprehensive evaluation of phosphoproteomic-based kinase activity inference. Nature Communications. 16(1). 4771–4771.
2.
Türei, Dénes, Olga Ivanova, Sophia Müller‐Dott, et al.. (2025). NetworkCommons: bridging data, knowledge, and methods to build and evaluate context-specific biological networks. Bioinformatics. 41(2). 1 indexed citations
3.
Müller‐Dott, Sophia, et al.. (2024). PhosX: data-driven kinase activity inference from phosphoproteomics experiments. Bioinformatics. 40(12). 2 indexed citations
4.
Müller‐Dott, Sophia, Eirini Tsirvouli, Miguél Vázquez, et al.. (2023). Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities. Nucleic Acids Research. 51(20). 10934–10949. 91 indexed citations
5.
Badia-i-Mompel, Pau, Sophia Müller‐Dott, Rémi Trimbour, et al.. (2023). Gene regulatory network inference in the era of single-cell multi-omics. Nature Reviews Genetics. 24(11). 739–754. 174 indexed citations breakdown →
6.
Arnold, Christian, Annique Claringbould, Nila H. Servaas, et al.. (2023). GRaNIE and GRaNPA : inference and evaluation of enhancer‐mediated gene regulatory networks. Molecular Systems Biology. 19(6). e11627–e11627. 31 indexed citations
7.
Šalovská, Barbora, Sophia Müller‐Dott, Wenxue Li, et al.. (2023). Phosphoproteomic analysis of metformin signaling in colorectal cancer cells elucidates mechanism of action and potential therapeutic opportunities. Clinical and Translational Medicine. 13(2). e1179–e1179. 15 indexed citations
8.
Wolf, Stephanie D., Christian Ehlting, Sophia Müller‐Dott, et al.. (2023). Hepatocytes reprogram liver macrophages involving control of TGF-β activation, influencing liver regeneration and injury. Hepatology Communications. 7(8). 9 indexed citations
9.
Badia-i-Mompel, Pau, Jana M. Braunger, Celina Geiß, et al.. (2022). decoupleR: ensemble of computational methods to infer biological activities from omics data. PubMed. 2(1). vbac016–vbac016. 302 indexed citations breakdown →

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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