Jaroslav Mareš

654 total citations
19 papers, 294 citations indexed

About

Jaroslav Mareš is a scholar working on Molecular Biology, Surgery and Cell Biology. According to data from OpenAlex, Jaroslav Mareš has authored 19 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Surgery and 3 papers in Cell Biology. Recurrent topics in Jaroslav Mareš's work include Bladder and Urothelial Cancer Treatments (5 papers), Urinary and Genital Oncology Studies (3 papers) and Pancreatic function and diabetes (3 papers). Jaroslav Mareš is often cited by papers focused on Bladder and Urothelial Cancer Treatments (5 papers), Urinary and Genital Oncology Studies (3 papers) and Pancreatic function and diabetes (3 papers). Jaroslav Mareš collaborates with scholars based in Czechia, Sweden and United States. Jaroslav Mareš's co-authors include Michael Welsh, Vı́tězslav Křı́ž, Nina S. Funa, Heinz H. Schmeiser, Gabriela Calounova, Kateřina Levová, Eva Frei, Marie Stiborová, Marko Babjuk and Torbjörn Karlsson and has published in prestigious journals such as Journal of Biological Chemistry, Cancer Research and International Journal of Cancer.

In The Last Decade

Jaroslav Mareš

16 papers receiving 283 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaroslav Mareš Czechia 11 145 102 58 46 46 19 294
Michio Oda Japan 11 116 0.8× 136 1.3× 35 0.6× 45 1.0× 17 0.4× 18 411
Ewoud N. Speksnijder Netherlands 11 288 2.0× 19 0.2× 36 0.6× 125 2.7× 17 0.4× 15 470
Julio C. Reséndiz Finland 10 69 0.5× 85 0.8× 11 0.2× 17 0.4× 21 0.5× 14 396
Jun Qi China 7 151 1.0× 77 0.8× 28 0.5× 54 1.2× 9 0.2× 17 347
Renwang Liu China 10 74 0.5× 18 0.2× 13 0.2× 52 1.1× 17 0.4× 26 259
Jianchao Wang China 13 203 1.4× 20 0.2× 14 0.2× 136 3.0× 42 0.9× 34 381
Yidong Zhou China 11 187 1.3× 42 0.4× 13 0.2× 157 3.4× 25 0.5× 34 371
Julie Bélanger Canada 9 110 0.8× 107 1.0× 119 2.1× 92 2.0× 8 0.2× 9 381
Sook In Chung South Korea 11 198 1.4× 46 0.5× 16 0.3× 61 1.3× 8 0.2× 17 377
Wen‐Lian Chen China 10 262 1.8× 38 0.4× 8 0.1× 186 4.0× 11 0.2× 20 419

Countries citing papers authored by Jaroslav Mareš

Since Specialization
Citations

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

Fields of papers citing papers by Jaroslav Mareš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaroslav Mareš

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

All Works

19 of 19 papers shown
1.
Svobodová, Iveta, Aleš Hořínek, A. Brisuda, et al.. (2016). Comparison of MicroRNA Content in Plasma and Urine Indicates the Existence of a Transrenal Passage of Selected MicroRNAs. Advances in experimental medicine and biology. 924. 97–100. 7 indexed citations
2.
Brisuda, A., Viktor Soukup, Aleš Hořínek, et al.. (2015). Urinary Cell-Free DNA Quantification as Non-Invasive Biomarker in Patients with Bladder Cancer. Urologia Internationalis. 96(1). 25–31. 38 indexed citations
3.
Soukup, Viktor, et al.. (2013). Exprese genů BCL-2 a BAX-1 ve tkáni Ta, T1 uroteliálních karcinomů močového měchýře a jejich prognostický význam. 17(3). 204–209. 1 indexed citations
4.
Stiborová, Marie, Jaroslav Mareš, Kateřina Levová, et al.. (2011). Role of cytochromes P450 in metabolism of carcinogenic aristolochic acid I: evidence of their contribution to aristolochic acid I detoxication and activation in rat liver.. PubMed. 32 Suppl 1. 121–30. 14 indexed citations
5.
Levová, Kateřina, Michaela Moserová, Miroslav Šulc, et al.. (2011). Role of Cytochromes P450 1A1/2 in Detoxication and Activation of Carcinogenic Aristolochic Acid I: Studies with the Hepatic NADPH:Cytochrome P450 Reductase Null (HRN) Mouse Model. Toxicological Sciences. 121(1). 43–56. 51 indexed citations
6.
Funa, Nina S., Vı́tězslav Křı́ž, Guangxiang Zang, et al.. (2009). Dysfunctional Microvasculature as a Consequence of Shb Gene Inactivation Causes Impaired Tumor Growth. Cancer Research. 69(5). 2141–2148. 30 indexed citations
7.
Křı́ž, Vı́tězslav, Jaroslav Mareš, Parri Wentzel, et al.. (2007). Shb null allele is inherited with a transmission ratio distortion and causes reduced viability in utero. Developmental Dynamics. 236(9). 2485–2492. 24 indexed citations
8.
Schultz, Iman J., Kenneth Wester, Huub Straatman, et al.. (2006). Prediction of recurrence in Ta urothelial cell carcinoma by real‐time quantitative PCR analysis: A microarray validation study. International Journal of Cancer. 119(8). 1915–1919. 19 indexed citations
9.
Schultz, Iman J., Kenneth Wester, Huub Straatman, et al.. (2006). Gene Expression Analysis for the Prediction of Recurrence in Patients with Primary Ta Urothelial Cell Carcinoma. European Urology. 51(2). 416–423. 23 indexed citations
10.
Křı́ž, Vı́tězslav, et al.. (2006). The SHB Adapter Protein Is Required for Normal Maturation of Mesoderm during in Vitro Differentiation of Embryonic Stem Cells. Journal of Biological Chemistry. 281(45). 34484–34491. 13 indexed citations
11.
Trková, Marie, Marko Babjuk, J Dušková, et al.. (2005). Analysis of genetic events in 17p13 and 9p21 regions supports predominant monoclonal origin of multifocal and recurrent bladder cancer. Cancer Letters. 242(1). 68–76. 9 indexed citations
12.
Křı́ž, Vı́tězslav, et al.. (2003). The SHB adapter protein is required for efficient multilineage differentiation of mouse embryonic stem cells. Experimental Cell Research. 286(1). 40–56. 15 indexed citations
13.
Mareš, Jaroslav, Vı́tězslav Křı́ž, Andreas Weinhäusel, et al.. (2001). Methylation changes in promoter and enhancer regions of the WT1 gene in Wilms’ tumours. Cancer Letters. 166(2). 165–171. 16 indexed citations
14.
Mareš, Jaroslav, et al.. (1996). Control of SHB gene expression by protein phosphorylation. Cellular Signalling. 8(1). 55–58. 1 indexed citations
15.
Welsh, Michael, et al.. (1993). Genetic factors of importance for β‐cell proliferation. Diabetes/Metabolism Reviews. 9(1). 25–36. 20 indexed citations
16.
Mareš, Jaroslav, Lena Claesson‐Welsh, & Michael Welsh. (1992). A Chimera between Platelet-Derived Growth Factor β-Receptor and Fibroblast Growth Factor Receptor-1 Stimulates Pancreatic β-Cell. DNA Synthesis in the Presence of PDGF-BB. Growth Factors. 6(2). 93–101. 9 indexed citations
17.
Mareš, Jaroslav. (1982). Areas of attraction of industrial centres in CSR. Geografie. 87(2). 105–109.
18.
Mareš, Jaroslav. (1981). To the problem of the geographical potential. Geografie. 86(1). 38–43.
19.
Mareš, Jaroslav, et al.. (1979). Purification and properties of phosphoenolpyruvate carboxylase from green leaves of maize. Collection of Czechoslovak Chemical Communications. 44(6). 1835–1840. 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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