Daniela Pintérová

19 papers receiving 528 citations

Peers

Daniela Pintérová
Comparison fields: 5 of 93
  • Cancer Research 54
  • Biotechnology 32
  • Hepatology 27
  • Oncology 90
  • Immunology 71
Replace Toshiyoshi Fujiwara with:
Toshiyoshi Fujiwara Japan
Julian Heuberger Germany
F. Jon Geske United States
Miriam Corti United States
Daigo Azakami Japan
Robert R. Conroy United States
Christophe Lallemand France
Sherry T. Shu United States
Neung‐Seon Seo United States
Penelope Pelczar Germany
Daniela Pintérová relative to Toshiyoshi Fujiwara Japan Toshiyoshi Fujiwara's profile →
Citations per field
00.5×2×3.5×
Toshiyoshi Fujiwara · 1×
Citations per year

Countries citing papers authored by Daniela Pintérová

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Pintérová

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniela Pintérová, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniela Pintérová Line = papers co-authored together Daniela Pintérová links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1
A clinically relevant, syngeneic model of spontaneous, highly metastatic B16 mouse melanoma.
2010177
2 201162
3 200647
4 200638
5 200437
6 200635
7 200429
8
Circulating human prostate cancer cells from an orthotopic mouse model rapidly captured by immunomagnetic beads and imaged by GFP expression.
201128
9 200524
10
Circulating tumor cells in patients with breast cancer: monitoring chemotherapy success.
201512
11 200611
12 200511
13 20078
14 20055
15 20115
16 20044
17 20114
18 20114
19
Tail spontaneous metastatic mouse model: comparison of metastatic potential of orthotopic and heterotopic models imaged by GFP and RFP protein.
20121

About Daniela Pintérová

Daniela Pintérová is a scholar working on Biotechnology, Oncology, Cancer Research, Immunology and Genetics, having authored 19 papers that have together received 542 indexed citations. Recurring topics across this work include Cancer Research and Treatments (5 papers), Cancer Cells and Metastasis (4 papers), Diabetes and associated disorders (3 papers), Pancreatic function and diabetes (3 papers), Immune Cell Function and Interaction (3 papers), Metabolism, Diabetes, and Cancer (2 papers), Virus-based gene therapy research (2 papers) and Cancer, Hypoxia, and Metabolism (2 papers). The work is most often cited by research in Cancer Research (54 citations), Biotechnology (32 citations), Hepatology (27 citations), Oncology (90 citations) and Immunology (71 citations). Daniela Pintérová has collaborated with scholars based in Czechia, Poland and Denmark. Frequent co-authors include Katarína Kološtová, Vladimír Bobek, Martina Kubecova, Robert M. Hoffman, Grzegorz Kacprzak, Michael Boubelı́k, Jerzy Kołodziej, Marie Černá, Peter Novota and Michal Anděl. Their work appears in journals such as American Journal of Otolaryngology, Human Immunology, Clinical Genetics, Immunology Letters and Clinical & Experimental Metastasis.

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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