Katarzyna Stąpor
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- Protein Structure and Dynamics 35
- Machine Learning in Bioinformatics 9
- RNA and protein synthesis mechanisms 7
- Lipid Membrane Structure and Behavior 7
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- Enzyme Structure and Function 17
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- Proteins in Food Systems 5
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- Alzheimer's disease research and treatments 9
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- Retinal Imaging and Analysis 6
Katarzyna Stąpor
66 papers receiving 576 citations
Peers
Comparison fields: 5 of 127
- Molecular Biology 342
- Cognitive Neuroscience 67
- Artificial Intelligence 82
- Materials Chemistry 112
- Food Science 42
Countries citing papers authored by Katarzyna Stąpor
This map shows the geographic impact of Katarzyna Stąpor'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 Katarzyna Stąpor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katarzyna Stąpor more than expected).
Fields of papers citing papers by Katarzyna Stąpor
This network shows the impact of papers produced by Katarzyna Stąpor. 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 Katarzyna Stąpor. The network helps show where Katarzyna Stąpor may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Katarzyna Stąpor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 7 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 6 | |
| 8 | 2023 | 7 | |
| 9 | 2021 | 15 | |
| 10 | 2021 | 18 | |
| 11 | 2021 | 8 | |
| 12 | 2016 | 0 | |
| 13 | 2015 | 1 | |
| 14 | A combined SVM-RDA classifier for protein fold recognition | 2011 | 1 |
| 15 | Support vector clustering algorithm for identification of glaucoma in ophthalmology | 2006 | 1 |
| 16 | Kernel K-Means clustering algorithm for identification of glaucoma in ophthalmology | 2005 | 1 |
| 17 | Automatic analysis of fundus eye images using mathematical morphology and neural networks for supporting glaucoma diagnosis | 2004 | 5 |
| 18 | Automatic analysis of fundus eye images for detection of glaucomatous changes | 2003 | 0 |
| 19 | Integration of structural pattern recognition methods into knowledge-based framework. Application to geographic map image analysis | 2000 | 1 |
| 20 | Model-based recognition of polyhedral objects from single intensity image using aspect graph | 1999 | 3 |
About Katarzyna Stąpor
Katarzyna Stąpor is a scholar working on Molecular Biology, Physiology and Molecular Medicine, having authored 76 papers that have together received 590 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (35 papers), Enzyme Structure and Function (17 papers), Machine Learning in Bioinformatics (9 papers), Alzheimer's disease research and treatments (9 papers), RNA and protein synthesis mechanisms (7 papers), Lipid Membrane Structure and Behavior (7 papers), Retinal Imaging and Analysis (6 papers) and Proteins in Food Systems (5 papers). The work is most often cited by research in Molecular Biology (342 citations), Cognitive Neuroscience (67 citations) and Artificial Intelligence (82 citations). Katarzyna Stąpor has collaborated with scholars based in Poland, Germany and Slovakia. Frequent co-authors include Leszek Konieczny, Irena Roterman, Piotr Fabian, Mateusz Banach, Jacek M. Łęski, Salvador García, Michał Woźniak, Paweł Ksieniewicz, Marian Kotas and Damian Grabowski. Their work appears in journals such as International Journal of Molecular Sciences, Membranes, ACS Omega, BMC Bioinformatics and PLoS ONE.
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.