Jana Marková

3.9k total citations
84 papers, 1.5k citations indexed

About

Jana Marková is a scholar working on Pathology and Forensic Medicine, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Jana Marková has authored 84 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Pathology and Forensic Medicine, 34 papers in Pulmonary and Respiratory Medicine and 16 papers in Molecular Biology. Recurrent topics in Jana Marková's work include Lymphoma Diagnosis and Treatment (46 papers), Lung Cancer Treatments and Mutations (32 papers) and Acute Myeloid Leukemia Research (16 papers). Jana Marková is often cited by papers focused on Lymphoma Diagnosis and Treatment (46 papers), Lung Cancer Treatments and Mutations (32 papers) and Acute Myeloid Leukemia Research (16 papers). Jana Marková collaborates with scholars based in Czechia, Germany and Switzerland. Jana Marková's co-authors include Andreas Engert, Peter Borchmann, Volker Diehl, Richard Greil, Hans Theodor Eich, Michael Fuchs, Anthony D. Ho, Bernd Dörken, Andreas Rank and Bastian von Tresckow and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Jana Marková

76 papers receiving 1.5k 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 Marková Czechia 18 956 455 446 409 255 84 1.5k
Beate Klimm Germany 17 781 0.8× 473 1.0× 284 0.6× 339 0.8× 82 0.3× 32 1.1k
Andreas Hüttmann Germany 21 600 0.6× 523 1.1× 139 0.3× 138 0.3× 367 1.4× 66 1.7k
Yuko Hashimoto Japan 19 477 0.5× 517 1.1× 221 0.5× 109 0.3× 184 0.7× 114 1.3k
Graziella Cefalo Italy 27 228 0.2× 395 0.9× 747 1.7× 411 1.0× 434 1.7× 76 1.9k
D.P. Dearnaley United Kingdom 25 102 0.1× 378 0.8× 743 1.7× 359 0.9× 454 1.8× 56 2.2k
Richard R. Blough United States 15 233 0.2× 284 0.6× 272 0.6× 87 0.2× 362 1.4× 40 1.5k
Casilda Balmaceda United States 26 132 0.1× 846 1.9× 431 1.0× 719 1.8× 396 1.6× 51 2.4k
Salvatore Tumolo Italy 24 195 0.2× 937 2.1× 431 1.0× 127 0.3× 299 1.2× 106 1.8k
M. Frénay France 18 305 0.3× 469 1.0× 734 1.6× 491 1.2× 423 1.7× 42 2.4k
Christopher D. Turner United States 25 112 0.1× 513 1.1× 501 1.1× 402 1.0× 777 3.0× 67 2.5k

Countries citing papers authored by Jana Marková

Since Specialization
Citations

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

Fields of papers citing papers by Jana Marková

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jana Marková

This figure shows the co-authorship network connecting the top 25 collaborators of Jana Marková. A scholar is included among the top collaborators of Jana Marková 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 Marková. Jana Marková 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.
Marková, Jana, et al.. (2023). A novel germline hyperactivating JAK2 mutation L604F. Annals of Hematology. 102(10). 2725–2734.
2.
Gajdoš, Martin, et al.. (2023). Language impairment in Parkinson’s disease: fMRI study of sentence reading comprehension. Frontiers in Aging Neuroscience. 15. 1117473–1117473. 7 indexed citations
3.
Kuželová, Kateřina, Barbora Brodská, Jana Marková, et al.. (2022). NPM1 and DNMT3A mutations are associated with distinct blast immunophenotype in acute myeloid leukemia. OncoImmunology. 11(1). 2073050–2073050. 7 indexed citations
4.
Móciková, Heidi, et al.. (2020). Outcome of elderly patients with classical Hodgkin’s lymphoma. Leukemia Research. 90. 106311–106311. 7 indexed citations
5.
Březinová, Jana, et al.. (2019). ASXL1 gene alterations in patients with isolated 20q deletion. Neoplasma. 66(4). 627–630. 1 indexed citations
6.
Král, Zdeněk, Heidi Móciková, Jana Marková, et al.. (2019). Treatment of Relapsed/Refractory Hodgkin Lymphoma: Real-World Data from the Czech Republic and Slovakia. Journal of Cancer. 10(21). 5041–5048. 9 indexed citations
7.
Borchmann, Sven, Horst Müller, Heinz Haverkamp, et al.. (2018). Symptomatic osteonecrosis as a treatment complication in Hodgkin lymphoma: an analysis of the German Hodgkin Study Group (GHSG). Leukemia. 33(2). 439–446. 12 indexed citations
8.
Móciková, Heidi, Robert Pytlík, Jana Marková, et al.. (2015). Can Rituximab Improve the Outcome of Patients with Nodular Lymphocyte-Predominant Hodgkin's Lymphoma?. Acta Haematologica. 134(3). 187–192. 2 indexed citations
9.
Križanová, Oľga, Jana Marková, Karel Pacák, et al.. (2014). Triptolide induces apoptosis through the SERCA 3 upregulation in PC12 cells. General Physiology and Biophysics. 33(1). 137–144. 13 indexed citations
10.
Marková, Jana, Soňa Hudecová, Andrea Šoltýsová, et al.. (2013). Sodium/calcium exchanger is upregulated by sulfide signaling, forms complex with the β1 and β3 but not β2 adrenergic receptors, and induces apoptosis. Pflügers Archiv - European Journal of Physiology. 466(7). 1329–1342. 33 indexed citations
11.
Belada, David, Běla Malinová, David Feltl, et al.. (2013). The Role of Radiotherapy in the Treatment of Malignant Lymphomas – Recommendations of the Czech Lymphoma Study Group. Klinicka onkologie. 26(2). 99–109.
12.
Hay, Annette E., Beate Klimm, Bingshu E. Chen, et al.. (2013). An individual patient-data comparison of combined modality therapy and ABVD alone for patients with limited-stage Hodgkin lymphoma. Annals of Oncology. 24(12). 3065–3069. 27 indexed citations
13.
14.
Marková, Jana, Jana Březinová, K Michalová, et al.. (2011). Prognostic impact of DNMT3A mutations in patients with intermediate cytogenetic risk profile acute myeloid leukemia. European Journal Of Haematology. 88(2). 128–135. 58 indexed citations
15.
Marková, Jana, et al.. (2011). Estimation of molecular upper remission limit for monitoring minimal residual disease in peripheral blood of acute myeloid leukemia patients by WT1 expression. Experimental and Therapeutic Medicine. 3(1). 129–133. 10 indexed citations
16.
17.
Móciková, Heidi, Robert Pytlík, Jana Marková, et al.. (2011). Pre-transplant positron emission tomography in patients with relapsed Hodgkin lymphoma. Leukemia & lymphoma. 52(9). 1668–1674. 40 indexed citations
18.
Špaček, Martin, et al.. (2010). Can We Use EBV-DNA Monitoring to Predict Disease Relapse in EBV-Positive Hodgkin Lymphoma Patients?. Acta Haematologica. 124(1). 23–26. 1 indexed citations
19.
Marková, Jana, Carsten Kobe, Annette Plütschow, et al.. (2009). FDG–PET for assessment of early treatment response after four cycles of chemotherapy in patients with advanced-stage Hodgkin's lymphoma has a high negative predictive value. Annals of Oncology. 20(7). 1270–1274. 35 indexed citations
20.
Deckert‐Schlüter, M., Josef Marek, Jana Marková, et al.. (1998). Primary manifestation of Hodgkin's disease in the central nervous system. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 432(5). 477–481. 13 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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