This map shows the geographic impact of O Babuŝíková'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 O Babuŝíková with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites O Babuŝíková more than expected).
This network shows the impact of papers produced by O Babuŝíková. 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 O Babuŝíková. The network helps show where O Babuŝíková may publish in the future.
Co-authorship network of co-authors of O Babuŝíková
This figure shows the co-authorship network connecting the top 25 collaborators of O Babuŝíková.
A scholar is included among the top collaborators of O Babuŝíková 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 O Babuŝíková. O Babuŝíková is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Babuŝíková, O, et al.. (2006). The impact of cell heterogeneity and immunophenotypic changes on monitoring minimal residual disease in acute myeloid leukemia.. PubMed. 53(6). 500–6.14 indexed citations
5.
Babuŝíková, O, et al.. (2005). The value of dot plot patterns and leukemia-associated phenotypes in AML diagnosis by multiparameter flow cytometry.. PubMed. 52(6). 517–22.6 indexed citations
6.
Babuŝíková, O, et al.. (2004). Analysis of surface and cytoplasmic immunoglobulin light/heavy chains by flow cytometry using a lysed-whole-blood technique: Implications for the differential diagnosis of B-cell malignancies.. PubMed. 51(6). 422–30.4 indexed citations
7.
Babuŝíková, O, et al.. (1999). Flow cytometric analysis of some activation/proliferation markers on human thymocytes and their correlation with cell proliferation.. PubMed. 46(6). 349–55.1 indexed citations
8.
Babuŝíková, O, et al.. (1998). Immunophenotypic characteristics of T-acute lymphoblastic leukemia cells in relation to DPP IV enzyme expression.. PubMed. 45(4). 237–42.4 indexed citations
9.
Babuŝíková, O, et al.. (1996). Flow cytometric detection of some activation and proliferation markers in human hematopoietic cell lines.. PubMed. 43(6). 381–8.3 indexed citations
10.
Babuŝíková, O, et al.. (1996). The study of AgNOR proteins in leukemias: diagnostic value and correlation to S-phase cell fraction.. PubMed. 43(6). 397–401.7 indexed citations
11.
Babuŝíková, O, et al.. (1996). Some early differentiation markers detected in cytoplasm of pre-B cells by flow cytometry.. PubMed. 43(6). 373–9.1 indexed citations
Babuŝíková, O, et al.. (1991). Purine metabolism enzyme pattern, cytochemical characteristics and clinicopathologic features of CD10-positive childhood T-cell leukemia.. PubMed. 38(6). 595–602.1 indexed citations
16.
Nn, Tupitsyn, et al.. (1990). Clinical significance of standard CD assessment in acute leukemia.. PubMed. 37(4). 431–8.2 indexed citations
17.
Rychly, Joachim, et al.. (1984). Cell electrophoretic characterization of peripheral blood lymphocyte subpopulations enriched by rosette formation, from normal individuals and CLL patients.. PubMed. 31(1). 57–64.1 indexed citations
18.
Babuŝíková, O, et al.. (1978). Mutual relationship between total and active T lymphocytes in patients with malignant tumors.. PubMed. 25(1). 67–74.1 indexed citations
19.
Babuŝíková, O, et al.. (1975). Change in the proportion of T and B lymphocytes in human malignant neoplasia in relation to the clinical stage.. PubMed. 22(4). 413–21.4 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.