Anna Supernat

2.5k total citations
31 papers, 485 citations indexed

About

Anna Supernat is a scholar working on Cancer Research, Molecular Biology and Oncology. According to data from OpenAlex, Anna Supernat has authored 31 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cancer Research, 15 papers in Molecular Biology and 10 papers in Oncology. Recurrent topics in Anna Supernat's work include Cancer Genomics and Diagnostics (10 papers), Cancer-related molecular mechanisms research (9 papers) and Ovarian cancer diagnosis and treatment (6 papers). Anna Supernat is often cited by papers focused on Cancer Genomics and Diagnostics (10 papers), Cancer-related molecular mechanisms research (9 papers) and Ovarian cancer diagnosis and treatment (6 papers). Anna Supernat collaborates with scholars based in Poland, Netherlands and Norway. Anna Supernat's co-authors include Anna J. Żaczek, Wojciech Biernat, Sylwia Łapińska‐Szumczyk, Tomasz Stokowy, Hanna Majewska, Dariusz Wydra, Jacek Jassem, Vidar M. Steen, Piotr Czapiewski and Barbara Seroczyńska and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and British Journal of Cancer.

In The Last Decade

Anna Supernat

29 papers receiving 481 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anna Supernat Poland 14 265 197 145 53 51 31 485
Maria Scatolini Italy 13 310 1.2× 121 0.6× 226 1.6× 38 0.7× 58 1.1× 24 589
Akshata R. Udyavar United States 10 212 0.8× 77 0.4× 232 1.6× 18 0.3× 20 0.4× 26 455
Christian Bowman-Colin United States 11 833 3.1× 231 1.2× 541 3.7× 17 0.3× 234 4.6× 13 1.1k
Minghui Zhang China 12 321 1.2× 173 0.9× 132 0.9× 33 0.6× 21 0.4× 19 494
Todd Boren United States 9 431 1.6× 334 1.7× 114 0.8× 3 0.1× 23 0.5× 22 635
Tolib B. Sanni United States 8 495 1.9× 99 0.5× 195 1.3× 12 0.2× 24 0.5× 8 692
Sarah Croessmann United States 13 217 0.8× 239 1.2× 219 1.5× 8 0.2× 64 1.3× 26 492
Erwin Tomasich Austria 13 336 1.3× 187 0.9× 179 1.2× 6 0.1× 18 0.4× 31 547
J.P. Brouillet France 12 178 0.7× 224 1.1× 106 0.7× 6 0.1× 63 1.2× 14 382
Jason P.W. Carey United States 12 386 1.5× 101 0.5× 307 2.1× 3 0.1× 33 0.6× 13 582

Countries citing papers authored by Anna Supernat

Since Specialization
Citations

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

Fields of papers citing papers by Anna Supernat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Supernat

This figure shows the co-authorship network connecting the top 25 collaborators of Anna Supernat. A scholar is included among the top collaborators of Anna Supernat 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 Anna Supernat. Anna Supernat 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.
Richert, J R, Elżbieta Senkus, Sylwia Łapińska‐Szumczyk, et al.. (2024). Measurable morphological features of single circulating tumor cells in selected solid tumors—A pilot study. Cytometry Part A. 105(12). 883–892. 2 indexed citations
2.
3.
Giczewska, Anna, Laurine E. Wedekind, David P. Noske, et al.. (2023). Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures. Neuro-Oncology Advances. 5(1). vdad134–vdad134. 1 indexed citations
4.
Giczewska, Anna, Aslι Küçükosmanoğlu, Rogier C. Buijsman, et al.. (2023). Screening of predicted synergistic multi-target therapies in glioblastoma identifies new treatment strategies. Neuro-Oncology Advances. 5(1). vdad073–vdad073. 8 indexed citations
5.
Jassem, Jacek, Andrzej Czyżewski, Thomas Würdinger, et al.. (2023). Platelet-Based Liquid Biopsies through the Lens of Machine Learning. Cancers. 15(8). 2336–2336. 7 indexed citations
6.
Duchnowska, Renata, Anna Supernat, Rafał Pęksa, et al.. (2022). Pathway-level mutation analysis in primary high-grade serous ovarian cancer and matched brain metastases. Scientific Reports. 12(1). 20537–20537. 4 indexed citations
7.
Supernat, Anna, Marta Popęda, Myron G. Best, et al.. (2021). Transcriptomic landscape of blood platelets in healthy donors. Scientific Reports. 11(1). 15679–15679. 33 indexed citations
8.
Łuczkowska, Karolina, Anna Supernat, Jonas Bybjerg‐Grauholm, et al.. (2021). Bortezomib induces methylation changes in neuroblastoma cells that appear to play a significant role in resistance development to this compound. Scientific Reports. 11(1). 9846–9846. 10 indexed citations
9.
Montfort, Anne, Anna Piskorz, Anna Supernat, et al.. (2020). Combining measures of immune infiltration shows additive effect on survival prediction in high-grade serous ovarian carcinoma. British Journal of Cancer. 122(12). 1803–1810. 20 indexed citations
10.
Krzyżanowska, Dorota M., et al.. (2019). Selection of reference genes for measuring the expression of aiiO in Ochrobactrum quorumnocens A44 using RT-qPCR. Scientific Reports. 9(1). 13129–13129. 10 indexed citations
11.
Supernat, Anna, et al.. (2018). Comparison of three variant callers for human whole genome sequencing. Scientific Reports. 8(1). 17851–17851. 45 indexed citations
12.
Skrzypski, Marcin, Tomasz Stokowy, Grzegorz Stasiłojć, et al.. (2018). MiR-192 and miR-662 enhance chemoresistance and invasiveness of squamous cell lung carcinoma. Lung Cancer. 118. 111–118. 36 indexed citations
13.
Czaplińska, Dominika, Anna Supernat, Andrzej C. Składanowski, et al.. (2016). Interactions between FGFR2 and RSK2—implications for breast cancer prognosis. Tumor Biology. 37(10). 13721–13731. 15 indexed citations
14.
Supernat, Anna, et al.. (2016). HOTAIR in Relation to Epithelial-Mesenchymal Transition and Cancer Stem Cells in Molecular Subtypes of Endometrial Cancer. The International Journal of Biological Markers. 31(3). 245–251. 24 indexed citations
15.
Łapińska‐Szumczyk, Sylwia, Anna Supernat, Hanna Majewska, et al.. (2014). HER2‐Positive Endometrial Cancer Subtype Carries Poor Prognosis. Clinical and Translational Science. 7(6). 482–488. 22 indexed citations
16.
Supernat, Anna, Sylwia Łapińska‐Szumczyk, Hanna Majewska, et al.. (2014). Tumor Heterogeneity at Protein Level as an Independent Prognostic Factor in Endometrial Cancer. Translational Oncology. 7(5). 613–619. 23 indexed citations
17.
Supernat, Anna, Sylwia Łapińska‐Szumczyk, Hanna Majewska, et al.. (2013). A multimarker qPCR platform for the characterisation of endometrial cancer. Oncology Reports. 31(2). 1003–1013. 6 indexed citations
18.
Supernat, Anna, Sylwia Łapińska‐Szumczyk, Sambor Sawicki, et al.. (2012). Deregulation of RAD21 and RUNX1 expression in endometrial cancer. Oncology Letters. 4(4). 727–732. 23 indexed citations
19.
Żaczek, Anna J., Aleksandra Markiewicz, Anna Supernat, et al.. (2012). Prognostic Value of TOP2A Gene Amplification and Chromosome 17 Polysomy in Early Breast Cancer. Pathology & Oncology Research. 18(4). 885–894. 22 indexed citations
20.
Supernat, Anna, Aleksandra Markiewicz, Marzena Wełnicka-Jaśkiewicz, et al.. (2011). CD73 Expression as a Potential Marker of Good Prognosis in Breast Carcinoma. Applied immunohistochemistry & molecular morphology. 20(2). 103–107. 72 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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