Begoña Cánovas

1.3k total citations · 1 hit paper
8 papers, 677 citations indexed

About

Begoña Cánovas is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, Begoña Cánovas has authored 8 papers receiving a total of 677 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Computational Theory and Mathematics and 2 papers in Oncology. Recurrent topics in Begoña Cánovas's work include DNA Repair Mechanisms (3 papers), Computational Drug Discovery Methods (3 papers) and CRISPR and Genetic Engineering (2 papers). Begoña Cánovas is often cited by papers focused on DNA Repair Mechanisms (3 papers), Computational Drug Discovery Methods (3 papers) and CRISPR and Genetic Engineering (2 papers). Begoña Cánovas collaborates with scholars based in Spain, Switzerland and Italy. Begoña Cánovas's co-authors include Ángel R. Nebreda, Ana Igea, Ignacio Dolado, Patrick Aloy, Samira Jaeger, Víctor Alcalde, Modesto Orozco, Roger R. Gomis, Eva González‐Suárez and Michitaka Isoda and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Reviews Molecular Cell Biology.

In The Last Decade

Begoña Cánovas

7 papers receiving 671 citations

Hit Papers

Diversity and versatility of p38 kinase signalling in hea... 2021 2026 2022 2024 2021 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
Begoña Cánovas Spain 6 432 125 94 76 68 8 677
Constantin Busuioc Romania 5 430 1.0× 179 1.4× 135 1.4× 62 0.8× 35 0.5× 13 722
Minsoo Koh South Korea 13 391 0.9× 178 1.4× 109 1.2× 128 1.7× 27 0.4× 17 717
Kanamata Reddy United States 15 470 1.1× 163 1.3× 65 0.7× 45 0.6× 32 0.5× 27 706
Pui–Kei Wu United States 17 672 1.6× 142 1.1× 137 1.5× 66 0.9× 26 0.4× 28 909
Eunhye Oh South Korea 16 363 0.8× 275 2.2× 110 1.2× 54 0.7× 29 0.4× 31 703
Ying Cheng China 13 346 0.8× 127 1.0× 70 0.7× 63 0.8× 26 0.4× 33 716
Tony Eight Lin Taiwan 18 644 1.5× 220 1.8× 45 0.5× 53 0.7× 71 1.0× 60 881
Amal Kamal Abdel‐Aziz Egypt 18 438 1.0× 207 1.7× 75 0.8× 68 0.9× 37 0.5× 34 1.1k
Nuria Ajenjo Spain 9 423 1.0× 136 1.1× 81 0.9× 44 0.6× 21 0.3× 12 598
Linette Castillo‐Pichardo Puerto Rico 10 467 1.1× 131 1.0× 103 1.1× 35 0.5× 19 0.3× 19 753

Countries citing papers authored by Begoña Cánovas

Since Specialization
Citations

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

Fields of papers citing papers by Begoña Cánovas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Begoña Cánovas

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

All Works

8 of 8 papers shown
1.
Gatti, Marco, Hülya Doğan, Antônio Porro, et al.. (2025). The PIN1–p38–CtIP signalling axis protects stalled replication forks from deleterious degradation. Nucleic Acids Research. 53(7).
2.
Gay, Marina, et al.. (2023). Characterization of p38α Signaling Networks in Cancer Cells Using Quantitative Proteomics and Phosphoproteomics. Molecular & Cellular Proteomics. 22(4). 100527–100527. 5 indexed citations
3.
González, Laura, Ana Domingo-Muelas, Petra Mikolčević, et al.. (2023). The atypical CDK activator RingoA/Spy1 regulates exit from quiescence in neural stem cells. iScience. 26(3). 106202–106202. 3 indexed citations
4.
Gutiérrez, Nuria Martí, Monica Cubillos‐Rojas, Begoña Cánovas, et al.. (2021). MK2 degradation as a sensor of signal intensity that controls stress-induced cell fate. Proceedings of the National Academy of Sciences. 118(29). 12 indexed citations
5.
Cánovas, Begoña & Ángel R. Nebreda. (2021). Diversity and versatility of p38 kinase signalling in health and disease. Nature Reviews Molecular Cell Biology. 22(5). 346–366. 404 indexed citations breakdown →
6.
Cánovas, Begoña, Ana Igea, Alessandro A. Sartori, et al.. (2018). Targeting p38α Increases DNA Damage, Chromosome Instability, and the Anti-tumoral Response to Taxanes in Breast Cancer Cells. Cancer Cell. 33(6). 1094–1110.e8. 70 indexed citations
7.
Jaeger, Samira, Ana Igea, Víctor Alcalde, et al.. (2016). Quantification of Pathway Cross-talk Reveals Novel Synergistic Drug Combinations for Breast Cancer. Cancer Research. 77(2). 459–469. 64 indexed citations
8.
Igea, Ana, et al.. (2013). Inhibition of p38 MAPK sensitizes tumour cells to cisplatin‐induced apoptosis mediated by reactive oxygen species and JNK. EMBO Molecular Medicine. 5(11). 1759–1774. 119 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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