Jana Procházková

545 total citations
25 papers, 384 citations indexed

About

Jana Procházková is a scholar working on Hematology, Molecular Biology and Immunology. According to data from OpenAlex, Jana Procházková has authored 25 papers receiving a total of 384 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Hematology, 5 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in Jana Procházková's work include Blood Coagulation and Thrombosis Mechanisms (8 papers), DNA Repair Mechanisms (4 papers) and Platelet Disorders and Treatments (4 papers). Jana Procházková is often cited by papers focused on Blood Coagulation and Thrombosis Mechanisms (8 papers), DNA Repair Mechanisms (4 papers) and Platelet Disorders and Treatments (4 papers). Jana Procházková collaborates with scholars based in Czechia, Austria and Armenia. Jana Procházková's co-authors include Kateřina Pokorná, Vladimı́r Holáň, Magdaléna Krulová, Alena Zajı́cová, Luděk Slavík, Peter Trošan, Eliška Svobodová, Joanna I. Loizou, Martin Procházka and Marc Wiedner and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Immunology and International Journal of Molecular Sciences.

In The Last Decade

Jana Procházková

22 papers receiving 376 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jana Procházková Czechia 12 109 99 98 66 59 25 384
Jacopo Olivieri Italy 11 56 0.5× 75 0.8× 81 0.8× 134 2.0× 74 1.3× 24 374
Jennifer Reed United States 7 125 1.1× 105 1.1× 22 0.2× 31 0.5× 101 1.7× 13 355
Michele Santodirocco Italy 11 67 0.6× 107 1.1× 163 1.7× 137 2.1× 36 0.6× 19 445
Birol Güvenç Türkiye 13 47 0.4× 105 1.1× 173 1.8× 169 2.6× 43 0.7× 57 445
Eugenia Rosa Nuzzolo Italy 11 81 0.7× 250 2.5× 121 1.2× 112 1.7× 46 0.8× 15 477
Chieko Aoki Japan 10 134 1.2× 135 1.4× 22 0.2× 53 0.8× 116 2.0× 15 440
O. Yu. Leplina Russia 12 166 1.5× 76 0.8× 111 1.1× 21 0.3× 64 1.1× 56 361
Jane Hudson United States 8 86 0.8× 142 1.4× 95 1.0× 49 0.7× 68 1.2× 11 393
Justyna Rak France 11 187 1.7× 184 1.9× 69 0.7× 191 2.9× 40 0.7× 19 531
Xiangli Xiao United States 8 171 1.6× 164 1.7× 57 0.6× 71 1.1× 63 1.1× 11 503

Countries citing papers authored by Jana Procházková

Since Specialization
Citations

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

Fields of papers citing papers by Jana Procházková

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jana Procházková

This figure shows the co-authorship network connecting the top 25 collaborators of Jana Procházková. A scholar is included among the top collaborators of Jana Procházková 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 Jana Procházková. Jana Procházková 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
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Procházková, Jana, et al.. (2021). Evaluation of the Determination of Dabigatran, Rivaroxaban, and Apixaban in Lupus Anticoagulant-Positive Patients. Diagnostics. 11(11). 2027–2027. 4 indexed citations
4.
Slavík, Luděk, et al.. (2021). Current Promising Biomarkers and Methods in the Diagnostics of Antiphospholipid Syndrome: A Review. Biomedicines. 9(2). 166–166. 24 indexed citations
5.
Slavík, Luděk, et al.. (2016). Possibility of Coagulation System Activation Determination with Tissue Factor in Pregnancy Complications. Clinical Laboratory. 62(10/2016). 1851–1856. 3 indexed citations
6.
Mazouzi, Abdelghani, Alexey Stukalov, André C. Müller, et al.. (2016). A Comprehensive Analysis of the Dynamic Response to Aphidicolin-Mediated Replication Stress Uncovers Targets for ATM and ATMIN. Cell Reports. 15(4). 893–908. 25 indexed citations
7.
Procházková, Jana & Joanna I. Loizou. (2015). Programmed DNA breaks in lymphoid cells: repair mechanisms and consequences in human disease. Immunology. 147(1). 11–20. 12 indexed citations
8.
Procházka, Martin, Jana Procházková, Marek Ľubušký, et al.. (2015). Markers of Endothelial Activation in Preeclampsia. Clinical Laboratory. 61(01+02/2015). 39–46. 24 indexed citations
9.
Procházková, Jana, Shinya Sakaguchi, Abdelghani Mazouzi, et al.. (2015). DNA Repair Cofactors ATMIN and NBS1 Are Required to Suppress T Cell Activation. PLoS Genetics. 11(11). e1005645–e1005645. 12 indexed citations
10.
Procházková, Jana, et al.. (2015). The role of tissue factor in normal pregnancy and in the development of preeclampsia: A review. Biomedical Papers. 159(2). 192–196. 13 indexed citations
11.
Slavík, Luděk, et al.. (2015). Polymorphism of the Fcγ Receptor II as a Possible Predisposing Factor for Heparin-Induced Thrombocytopenia. Clinical Laboratory. 61(08/2015). 1027–32. 4 indexed citations
12.
Wiedner, Marc, et al.. (2014). ATMIN is required for the ATM-mediated signaling and recruitment of 53BP1 to DNA damage sites upon replication stress. DNA repair. 24. 122–130. 23 indexed citations
13.
Svobodová, Eliška, Magdaléna Krulová, Alena Zajı́cová, et al.. (2011). The Role of Mouse Mesenchymal Stem Cells in Differentiation of Naive T-Cells into Anti-Inflammatory Regulatory T-Cell or Proinflammatory Helper T-Cell 17 Population. Stem Cells and Development. 21(6). 901–910. 95 indexed citations
14.
Slavík, Luděk, et al.. (2011). THE PATHOPHYSIOLOGY OF ENDOTHELIAL FUNCTION IN PREGNANCY AND THE USEFULNESS OF ENDOTHELIAL MARKERS. Biomedical Papers. 155(4). 333–337. 11 indexed citations
15.
Procházková, Jana, Kateřina Pokorná, & Vladimı́r Holáň. (2011). IL-12 inhibits the TGF-β-dependent T cell developmental programs and skews the TGF-β-induced differentiation into a Th1-like direction. Immunobiology. 217(1). 74–82. 52 indexed citations
16.
Holáň, Vladimı́r, Kateřina Pokorná, Jana Procházková, Magdaléna Krulová, & Alena Zajı́cová. (2010). Immunoregulatory Properties of Mouse Limbal Stem Cells. The Journal of Immunology. 184(4). 2124–2129. 21 indexed citations
17.
Fiala, Ondřej, Lenka Pospíšilová, Jana Procházková, et al.. (2010). Parkin mutations and phenotypic features in Czech patients with early-onset Parkinson's disease.. PubMed. 31(2). 187–92. 5 indexed citations
18.
Slavík, Luděk, et al.. (2009). MOLECULAR PATHOPHYSIOLOGY OF THROMBOTIC STATES AND THEIR IMPACT TO LABORATORY DIAGNOSTICS. Biomedical Papers. 153(1). 19–25. 10 indexed citations
19.
Procházková, Jana, Jan Frič, Kateřina Pokorná, et al.. (2009). Distinct regulatory roles of transforming growth factor‐β and interleukin‐4 in the development and maintenance of natural and induced CD4+ CD25+ Foxp3+ regulatory T cells. Immunology. 128(1pt2). e670–8. 22 indexed citations
20.
Bureš, Petr, Petr Šmarda, Sara Fuentes‐Soriano, et al.. (2007). Correlation between GC content ond genome size in plants. Cytometry. 3 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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