Miroslav Kubeš

620 total citations
10 papers, 479 citations indexed

About

Miroslav Kubeš is a scholar working on Molecular Biology, Public Health, Environmental and Occupational Health and Hematology. According to data from OpenAlex, Miroslav Kubeš has authored 10 papers receiving a total of 479 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Public Health, Environmental and Occupational Health and 3 papers in Hematology. Recurrent topics in Miroslav Kubeš's work include Acute Myeloid Leukemia Research (3 papers), Acute Lymphoblastic Leukemia research (3 papers) and DNA Repair Mechanisms (2 papers). Miroslav Kubeš is often cited by papers focused on Acute Myeloid Leukemia Research (3 papers), Acute Lymphoblastic Leukemia research (3 papers) and DNA Repair Mechanisms (2 papers). Miroslav Kubeš collaborates with scholars based in Slovakia, France and United States. Miroslav Kubeš's co-authors include Hervé Chneiweiss, Jocelyne Cordier, M Blaŝko, Dušan Bakoš, Ľuboš Danišovič, Jacques Glowinski, Jean‐Antoine Girault, B. Canton, J. Głowiński and Guohua Pan and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and Journal of Neurochemistry.

In The Last Decade

Miroslav Kubeš

9 papers receiving 471 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Miroslav Kubeš 290 127 93 87 57 10 479
Grigorios Tsaknakis 238 0.8× 115 0.9× 77 0.8× 43 0.5× 47 0.8× 17 516
Hisako Ishimine 299 1.0× 145 1.1× 44 0.5× 39 0.4× 30 0.5× 16 587
Barbara Leutgeb 390 1.3× 67 0.5× 91 1.0× 31 0.4× 61 1.1× 8 674
Nicola Pierobon 297 1.0× 276 2.2× 50 0.5× 21 0.2× 71 1.2× 7 601
Nilanjana Sengupta 425 1.5× 67 0.5× 69 0.7× 18 0.2× 40 0.7× 19 669
Usha Nagavarapu 343 1.2× 55 0.4× 94 1.0× 19 0.2× 57 1.0× 13 611
Charito S. Buensuceso 397 1.4× 65 0.5× 53 0.6× 16 0.2× 130 2.3× 10 866
Menglei Yu 194 0.7× 99 0.8× 106 1.1× 14 0.2× 26 0.5× 19 468
Nidal Boulos 424 1.5× 225 1.8× 101 1.1× 22 0.3× 59 1.0× 23 720

Countries citing papers authored by Miroslav Kubeš

Since Specialization
Citations

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

Fields of papers citing papers by Miroslav Kubeš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miroslav Kubeš

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

All Works

10 of 10 papers shown
1.
Škorvaga, Milan, et al.. (2021). Induction of AML Preleukemic Fusion Genes in HSPCs and DNA Damage Response in Preleukemic Fusion Gene Positive Samples. Antioxidants. 10(3). 481–481. 4 indexed citations
3.
Škorvaga, Milan, et al.. (2014). Incidence of Common Preleukemic Gene Fusions in Umbilical Cord Blood in Slovak Population. PLoS ONE. 9(3). e91116–e91116. 22 indexed citations
4.
Kubeš, Miroslav, et al.. (2012). DNA damage response in CD133 + stem/progenitor cells from umbilical cord blood: Low level of endogenous foci and high recruitment of 53BP1. International Journal of Radiation Biology. 89(4). 301–309. 25 indexed citations
5.
Slovinská, Lucia, Miroslav Kubeš, J Radoňák, et al.. (2011). Umbilical Cord Blood Cells CD133+/CD133− Cultivation in Neural Proliferation Media Differentiates Towards Neural Cell Lineages. Archives of Medical Research. 42(7). 555–562. 4 indexed citations
6.
Ihnatko, Robert, Miroslav Kubeš, Martina Takáčová, et al.. (2006). Extracellular acidosis elevates carbonic anhydrase IX in human glioblastoma cells via transcriptional modulation that does not depend on hypoxia. International Journal of Oncology. 29(4). 1025–33. 75 indexed citations
7.
Danišovič, Ľuboš, et al.. (2006). Autologous biograft and mesenchymal stem cells in treatment of the diabetic foot.. PubMed. 27 Suppl 2. 134–7. 146 indexed citations
8.
Kitsberg, Daniel, Étienne Formstecher, Mireille Fauquet, et al.. (1999). Knock-Out of the Neural Death Effector Domain Protein PEA-15 Demonstrates That Its Expression Protects Astrocytes from TNFα-Induced Apoptosis. Journal of Neuroscience. 19(19). 8244–8251. 122 indexed citations
9.
Kubeš, Miroslav, Jocelyne Cordier, Jacques Glowinski, Jean‐Antoine Girault, & Hervé Chneiweiss. (1998). Endothelin Induces a Calcium‐Dependent Phosphorylation of PEA‐15 in Intact Astrocytes: Identification of Ser104 and Ser116 Phosphorylated, Respectively, by Protein Kinase C and Calcium/Calmodulin Kinase II In Vitro. Journal of Neurochemistry. 71(3). 1307–1314. 77 indexed citations
10.
Kubeš, Miroslav, et al.. (1993). Masking of HLA class I molecules expressed on K-562 target cells can restore their susceptibility to NK cell cytolysis. Immunobiology. 188(1-2). 134–144. 4 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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