Kinga Pajdzik
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
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- RNA modifications and cancer
- RNA Research and Splicing
- Cancer-related gene regulation
- RNA and protein synthesis mechanisms
- Epigenetics and DNA Methylation
- RNA regulation and disease
Papers in
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- RNA modifications and cancer 10
- Epigenetics and DNA Methylation 3
- RNA and protein synthesis mechanisms 3
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- Cancer-related molecular mechanisms research 4
- Co-authors
- Qing Dai (9 shared papers)Chuan He (8 shared papers)Yunhee Kang (1 shared paper)Zhenxing Guo (1 shared paper)Yangping Li (1 shared paper)Peng Jin (1 shared paper)Hao Wu (1 shared paper)Emily G. Allen (1 shared paper)
- Journals
- Nature Communications (1 paper)Genome biology (1 paper)IUBMB Life (1 paper)Nature Biotechnology (1 paper)RNA (1 paper)
- Partner nations
- United StatesChinaPoland
In The Last Decade
Kinga Pajdzik
13 papers receiving 629 citations
Kinga Pajdzik's Hit Papers
Peers
Comparison fields: 5 of 53
- Cancer Research 197
- Molecular Biology 549
- Neurology 14
- Aging 3
- Oncology 36
Countries citing papers authored by Kinga Pajdzik
This map shows the geographic impact of Kinga Pajdzik'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 Kinga Pajdzik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kinga Pajdzik more than expected).
Fields of papers citing papers by Kinga Pajdzik
This network shows the impact of papers produced by Kinga Pajdzik. 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 Kinga Pajdzik. The network helps show where Kinga Pajdzik may publish in the future.
Co-authors
The 25 scholars most cited alongside Kinga Pajdzik, 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 | 2021 | 191 | |
| 2 | Quantitative sequencing using BID-seq uncovers abundant pseudouridines in mammalian mRNA at base resolution Hit paper breakdown → | 2022 | 164 |
| 3 | 2021 | 142 | |
| 4 | 2023 | 57 | |
| 5 | 2021 | 13 | |
| 6 | 2019 | 11 | |
| 7 | 2024 | 9 | |
| 8 | 2020 | 9 | |
| 9 | 2020 | 9 | |
| 10 | 2024 | 8 | |
| 11 | 2024 | 8 | |
| 12 | 2022 | 7 | |
| 13 | 2023 | 6 | |
| 14 | 2025 | 0 | |
| 15 | The influence of heavy metals on Phaeodactylum tricornutum growth : a preliminary study | 2016 | 0 |
About Kinga Pajdzik
Kinga Pajdzik is a scholar working on Molecular Biology, Cancer Research, Paleontology, Pharmacology and Oncology, having authored 15 papers that have together received 634 indexed citations. Recurring topics across this work include RNA modifications and cancer (10 papers), Cancer-related molecular mechanisms research (4 papers), Epigenetics and DNA Methylation (3 papers), RNA and protein synthesis mechanisms (3 papers), Paleontology and Stratigraphy of Fossils (1 paper), Endoplasmic Reticulum Stress and Disease (1 paper), Algal biology and biofuel production (1 paper) and Drug-Induced Adverse Reactions (1 paper). The work is most often cited by research in Cancer Research (197 citations), Molecular Biology (549 citations), Neurology (14 citations), Aging (3 citations) and Oncology (36 citations). Kinga Pajdzik has collaborated with scholars based in United States, China and Poland. Frequent co-authors include Qing Dai, Chuan He, Yunhee Kang, Zhenxing Guo, Yangping Li, Peng Jin, Hao Wu, Emily G. Allen, Bing Yao and Ranhui Duan. Their work appears in journals such as Nature Communications, Genome biology, IUBMB Life, Nature Biotechnology and RNA.
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.