Lenka Munoz

2.5k total citations
38 papers, 2.0k citations indexed

About

Lenka Munoz is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Lenka Munoz has authored 38 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 8 papers in Immunology and 7 papers in Oncology. Recurrent topics in Lenka Munoz's work include Melanoma and MAPK Pathways (7 papers), Microtubule and mitosis dynamics (6 papers) and Ubiquitin and proteasome pathways (5 papers). Lenka Munoz is often cited by papers focused on Melanoma and MAPK Pathways (7 papers), Microtubule and mitosis dynamics (6 papers) and Ubiquitin and proteasome pathways (5 papers). Lenka Munoz collaborates with scholars based in Australia, United States and Germany. Lenka Munoz's co-authors include Alaina J. Ammit, Ariadna Recasens, Thomas Grewal, Ramzi H. Abbassi, Michael Kassiou, Terrance G. Johns, D. Martin Watterson, Wenhui Hu, Saktimayee M. Roy and Linda J. Van Eldik and has published in prestigious journals such as Nature Communications, Nature Reviews Drug Discovery and Analytical Biochemistry.

In The Last Decade

Lenka Munoz

38 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lenka Munoz Australia 20 1.0k 369 297 259 257 38 2.0k
Daret St. Clair United States 21 1.5k 1.5× 470 1.3× 452 1.5× 574 2.2× 171 0.7× 51 2.8k
Chiara Giacomelli Italy 25 800 0.8× 259 0.7× 178 0.6× 269 1.0× 132 0.5× 78 1.6k
Anna Carolina Carvalho da Fonseca Brazil 20 780 0.8× 225 0.6× 165 0.6× 180 0.7× 448 1.7× 40 1.9k
Zhou Zhu China 32 1.8k 1.7× 885 2.4× 500 1.7× 481 1.9× 158 0.6× 93 3.6k
Kaori Nishikawa Japan 23 841 0.8× 151 0.4× 259 0.9× 167 0.6× 163 0.6× 44 1.7k
Jianhong Zhu China 30 1.4k 1.4× 241 0.7× 159 0.5× 368 1.4× 179 0.7× 78 2.5k
Ricardo Gargini Spain 22 696 0.7× 201 0.5× 317 1.1× 142 0.5× 120 0.5× 46 1.3k
Zhulun Wang United States 17 1.2k 1.2× 183 0.5× 397 1.3× 175 0.7× 297 1.2× 27 2.0k
Yichin Liu United States 21 1.3k 1.3× 404 1.1× 401 1.4× 108 0.4× 116 0.5× 33 2.3k
Barbara Becattini Sweden 19 1.2k 1.2× 201 0.5× 260 0.9× 120 0.5× 156 0.6× 32 1.9k

Countries citing papers authored by Lenka Munoz

Since Specialization
Citations

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

Fields of papers citing papers by Lenka Munoz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lenka Munoz

This figure shows the co-authorship network connecting the top 25 collaborators of Lenka Munoz. A scholar is included among the top collaborators of Lenka Munoz 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 Lenka Munoz. Lenka Munoz 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.
Janowicz, Phillip W., Brett W. Stringer, Marie Zhang, et al.. (2025). Enhanced detection of glioblastoma vasculature with superparamagnetic iron oxide nanoparticles and MRI. Scientific Reports. 15(1). 14283–14283. 2 indexed citations
2.
Baker, Jennifer R., et al.. (2023). Systematic literature review reveals suboptimal use of chemical probes in cell-based biomedical research. Nature Communications. 14(1). 3228–3228. 15 indexed citations
3.
Hoque, Monira, Ariadna Recasens, Ramzi H. Abbassi, et al.. (2021). MerTK activity is not necessary for the proliferation of glioblastoma stem cells. Biochemical Pharmacology. 186. 114437–114437. 3 indexed citations
4.
Recasens, Ariadna, Sean J. Humphrey, M. A. Ellis, et al.. (2021). Global phosphoproteomics reveals DYRK1A regulates CDK1 activity in glioblastoma cells. Cell Death Discovery. 7(1). 81–81. 35 indexed citations
5.
Recasens, Ariadna & Lenka Munoz. (2019). Targeting Cancer Cell Dormancy. Trends in Pharmacological Sciences. 40(2). 128–141. 241 indexed citations
6.
Winnischofer, Sheila Maria Brochado, et al.. (2018). Anti-proliferative and cytotoxic activities of the flavonoid isoliquiritigenin in the human neuroblastoma cell line SH-SY5Y. Chemico-Biological Interactions. 299. 77–87. 30 indexed citations
7.
Munoz, Lenka. (2017). Non-kinase targets of protein kinase inhibitors. Nature Reviews Drug Discovery. 16(6). 424–440. 100 indexed citations
8.
Munoz, Lenka, Yiu To Yeung, & Thomas Grewal. (2016). Oncogenic Ras modulates p38 MAPK-mediated inflammatory cytokine production in glioblastoma cells. Cancer Biology & Therapy. 17(4). 355–363. 19 indexed citations
9.
Browne, Stephen, Mia C. Åkerfeldt, Christian Peifer, et al.. (2015). Pharmacology of novel small-molecule tubulin inhibitors in glioblastoma cells with enhanced EGFR signalling. Biochemical Pharmacology. 98(4). 587–601. 16 indexed citations
10.
Heng, Benjamin, Chi Huey Wong, Seray Adams, et al.. (2015). Cytotoxic activity of the MK2 inhibitor CMPD1 in glioblastoma cells is independent of MK2. Cell Death Discovery. 1(1). 15028–15028. 18 indexed citations
11.
Abbassi, Ramzi H., Terrance G. Johns, Michael Kassiou, & Lenka Munoz. (2015). DYRK1A in neurodegeneration and cancer: Molecular basis and clinical implications. Pharmacology & Therapeutics. 151. 87–98. 124 indexed citations
12.
Yeung, Yiu To, Benjamin Heng, Michael E. Buckland, et al.. (2014). The p38-MK2-HuR pathway potentiates EGFRvIII–IL-1β-driven IL-6 secretion in glioblastoma cells. Oncogene. 34(22). 2934–2942. 65 indexed citations
13.
14.
15.
Yeung, Yiu To, Nicole S. Bryce, Seray Adams, et al.. (2012). p38 MAPK inhibitors attenuate pro-inflammatory cytokine production and the invasiveness of human U251 glioblastoma cells. Journal of Neuro-Oncology. 109(1). 35–44. 80 indexed citations
16.
Munoz, Lenka, Emma E. Ramsay, Qi Ge, et al.. (2010). Novel p38 MAPK inhibitor ML3403 has potent anti-inflammatory activity in airway smooth muscle. European Journal of Pharmacology. 635(1-3). 212–218. 28 indexed citations
17.
Munoz, Lenka, et al.. (2010). Fluorescence polarization binding assay to develop inhibitors of inactive p38α mitogen-activated protein kinase. Analytical Biochemistry. 401(1). 125–133. 19 indexed citations
18.
Munoz, Lenka, Hantamalala Ralay Ranaivo, Saktimayee M. Roy, et al.. (2007). A novel p38α MAPK inhibitor suppresses brain proinflammatory cytokine up-regulation and attenuates synaptic dysfunction and behavioral deficits in an Alzheimer's disease mouse model. Journal of Neuroinflammation. 4(1). 21–21. 197 indexed citations
19.
Hu, Wenhui, Hantamalala Ralay Ranaivo, Saktimayee M. Roy, et al.. (2006). Development of a novel therapeutic suppressor of brain proinflammatory cytokine up-regulation that attenuates synaptic dysfunction and behavioral deficits. Bioorganic & Medicinal Chemistry Letters. 17(2). 414–418. 56 indexed citations
20.
Gündisch, Daniela, et al.. (2004). Synthesis and evaluation of phenylcarbamate derivatives as ligands for nicotinic acetylcholine receptors. Bioorganic & Medicinal Chemistry. 12(18). 4953–4962. 10 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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