Stefka Tyanova

18.8k total citations · 6 hit papers
25 papers, 11.8k citations indexed

About

Stefka Tyanova is a scholar working on Molecular Biology, Spectroscopy and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Stefka Tyanova has authored 25 papers receiving a total of 11.8k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 16 papers in Spectroscopy and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Stefka Tyanova's work include Advanced Proteomics Techniques and Applications (16 papers), Mass Spectrometry Techniques and Applications (8 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Stefka Tyanova is often cited by papers focused on Advanced Proteomics Techniques and Applications (16 papers), Mass Spectrometry Techniques and Applications (8 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Stefka Tyanova collaborates with scholars based in Germany, United States and Denmark. Stefka Tyanova's co-authors include Jüergen Cox, Matthias Mann, Jürgen Cox, Tamar Geiger, Pavel Sinitcyn, Marco Y. Hein, Kirti Sharma, Daniel N. Itzhak, Georg H. H. Borner and Rochelle C. J. D’Souza and has published in prestigious journals such as Nature Communications, Neuron and Nature Neuroscience.

In The Last Decade

Stefka Tyanova

24 papers receiving 11.8k citations

Hit Papers

The Perseus computational platform for comprehensive anal... 2014 2026 2018 2022 2016 2016 2014 2015 2016 1000 2.0k 3.0k 4.0k 5.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The Perseus computational platform for comprehensive analysis of (prote)omics data
    2016 5.4k citations Stefka Tyanova, Pavel Sinitcyn et al. Nature Methods profile →
  2. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
    2016 3.1k citations Stefka Tyanova, Jüergen Cox et al. Nature Protocols profile →
  3. Ultradeep Human Phosphoproteome Reveals a Distinct Regulatory Nature of Tyr and Ser/Thr-Based Signaling
    2014 750 citations Kirti Sharma, Rochelle C. J. D’Souza et al. Cell Reports profile →
  4. Cell type– and brain region–resolved mouse brain proteome
    2015 557 citations Kirti Sharma, Sebastian Schmitt et al. Nature Neuroscience profile →
  5. Global, quantitative and dynamic mapping of protein subcellular localization
    2016 421 citations Daniel N. Itzhak, Stefka Tyanova et al. eLife profile →
  6. Perseus: A Bioinformatics Platform for Integrative Analysis of Proteomics Data in Cancer Research
    2018 374 citations Stefka Tyanova, Jüergen Cox Methods in molecular biology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stefka Tyanova Germany 17 7.7k 2.2k 1.5k 1.1k 1.0k 25 11.8k
Tamar Geiger Israel 43 8.9k 1.1× 2.7k 1.2× 1.6k 1.0× 1.1k 1.0× 1.4k 1.3× 100 12.8k
Yasset Pérez‐Riverol United Kingdom 29 8.0k 1.0× 2.8k 1.3× 987 0.6× 1.0k 0.9× 838 0.8× 86 12.0k
Juan Antonio Vizcaíno United Kingdom 42 9.8k 1.3× 3.5k 1.6× 1.3k 0.8× 1.1k 1.0× 911 0.9× 127 14.4k
Martin R. Larsen Denmark 59 8.4k 1.1× 4.0k 1.8× 1.2k 0.8× 882 0.8× 955 0.9× 260 13.0k
Marco Y. Hein Germany 24 11.1k 1.4× 1.7k 0.8× 2.2k 1.4× 1.4k 1.3× 1.2k 1.2× 28 15.8k
Albert Sickmann Germany 72 11.0k 1.4× 3.1k 1.4× 1.6k 1.0× 914 0.8× 839 0.8× 320 15.9k
W. Hayes McDonald United States 55 8.6k 1.1× 1.7k 0.8× 2.0k 1.3× 691 0.6× 1.0k 1.0× 138 11.3k
Boris Maček Germany 55 10.7k 1.4× 3.6k 1.6× 1.6k 1.0× 1.1k 1.0× 1.1k 1.1× 203 14.7k
Alexandre Zougman United Kingdom 24 6.2k 0.8× 2.1k 1.0× 827 0.5× 763 0.7× 693 0.7× 36 9.3k
Nagarjuna Nagaraj Germany 30 11.9k 1.5× 4.5k 2.0× 2.0k 1.3× 1.3k 1.2× 1.2k 1.1× 39 17.2k

Countries citing papers authored by Stefka Tyanova

Since Specialization
Citations

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

Fields of papers citing papers by Stefka Tyanova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefka Tyanova

This figure shows the co-authorship network connecting the top 25 collaborators of Stefka Tyanova. A scholar is included among the top collaborators of Stefka Tyanova 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 Stefka Tyanova. Stefka Tyanova 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.
Paladini, Maria Serena, Kristof Törkenczy, Elma S. Frias, et al.. (2025). Fate mapping of peripherally-derived macrophages after traumatic brain injury in mice reveals a long-lasting population with a distinct transcriptomic signature. Nature Communications. 16(1). 8898–8898.
2.
Bacq, Alexandre, Juan A. Osés-Prieto, Stefka Tyanova, et al.. (2023). Targeted suppression of mTORC2 reduces seizures across models of epilepsy. Nature Communications. 14(1). 7364–7364. 9 indexed citations
3.
Xu, Tao, Ahmed Sawas, Wan‐Jen Hong, et al.. (2023). RWD-derived response in multiple myeloma. PLoS ONE. 18(5). e0285125–e0285125. 1 indexed citations
4.
Gutiérrez, Nuria Martí, Luise Wolf, Stefka Tyanova, et al.. (2022). DUSP4 protects BRAF- and NRAS-mutant melanoma from oncogene overdose through modulation of MITF. Life Science Alliance. 5(9). e202101235–e202101235. 8 indexed citations
5.
Pandya, Nikhil J., Sonja Meier, Stefka Tyanova, et al.. (2022). A cross-species spatiotemporal proteomic analysis identifies UBE3A-dependent signaling pathways and targets. Molecular Psychiatry. 27(5). 2590–2601. 14 indexed citations
6.
Iglesias‐Gato, Diego, Elin Thysell, Stefka Tyanova, et al.. (2018). The Proteome of Prostate Cancer Bone Metastasis Reveals Heterogeneity with Prognostic Implications. Clinical Cancer Research. 24(21). 5433–5444. 66 indexed citations
7.
Overmyer, Katherine A., Stefka Tyanova, Alex S. Hebert, et al.. (2018). Multiplexed proteome analysis with neutron-encoded stable isotope labeling in cells and mice. Nature Protocols. 13(2). 293–306. 34 indexed citations
8.
Tyanova, Stefka & Jüergen Cox. (2018). Perseus: A Bioinformatics Platform for Integrative Analysis of Proteomics Data in Cancer Research. Methods in molecular biology. 1711. 133–148. 374 indexed citations breakdown →
9.
Tyanova, Stefka, Pavel Sinitcyn, Marco Y. Hein, et al.. (2016). The Perseus computational platform for comprehensive analysis of (prote)omics data. Nature Methods. 13(9). 731–740. 5384 indexed citations breakdown →
10.
Itzhak, Daniel N., Stefka Tyanova, Jürgen Cox, & Georg H. H. Borner. (2016). Global, quantitative and dynamic mapping of protein subcellular localization. eLife. 5. 421 indexed citations breakdown →
11.
Tyanova, Stefka, Reidar Albrechtsen, Pauliina Kronqvist, et al.. (2016). Proteomic maps of breast cancer subtypes. Nature Communications. 7(1). 10259–10259. 233 indexed citations
12.
Coscia, Fabian, Karen M. Watters, Marion Curtis, et al.. (2016). Integrative proteomic profiling of ovarian cancer cell lines reveals precursor cell associated proteins and functional status. Nature Communications. 7(1). 12645–12645. 154 indexed citations
13.
Geyer, Philipp E., Nicolai J. Wewer Albrechtsen, Stefka Tyanova, et al.. (2016). Proteomics reveals the effects of sustained weight loss on the human plasma proteome. Molecular Systems Biology. 12(12). 901–901. 173 indexed citations
14.
Iglesias‐Gato, Diego, Pernilla Wikström, Stefka Tyanova, et al.. (2015). The Proteome of Primary Prostate Cancer. European Urology. 69(5). 942–952. 107 indexed citations
15.
Sharma, Kirti, Sebastian Schmitt, Caroline G. Bergner, et al.. (2015). Cell type– and brain region–resolved mouse brain proteome. Nature Neuroscience. 18(12). 1819–1831. 557 indexed citations breakdown →
16.
Deeb, Sally J., Stefka Tyanova, Michael Hummel, et al.. (2015). Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles. Molecular & Cellular Proteomics. 14(11). 2947–2960. 70 indexed citations
17.
Tyanova, Stefka, et al.. (2015). Visualization of LC‐MS/MS proteomics data in MaxQuant. PROTEOMICS. 15(8). 1453–1456. 181 indexed citations
18.
Tyanova, Stefka, Matthias Mann, & Jürgen Cox. (2014). MaxQuant for In-Depth Analysis of Large SILAC Datasets. Methods in molecular biology. 1188. 351–364. 66 indexed citations
19.
Sharma, Kirti, Rochelle C. J. D’Souza, Stefka Tyanova, et al.. (2014). Ultradeep Human Phosphoproteome Reveals a Distinct Regulatory Nature of Tyr and Ser/Thr-Based Signaling. Cell Reports. 8(5). 1583–1594. 750 indexed citations breakdown →
20.
Tyanova, Stefka, Jürgen Cox, Jesper V. Olsen, Matthias Mann, & Dmitrij Frishman. (2013). Phosphorylation Variation during the Cell Cycle Scales with Structural Propensities of Proteins. PLoS Computational Biology. 9(1). e1002842–e1002842. 50 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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