Anna Cichońska
Impact in
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- Computational Drug Discovery Methods
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- Metabolomics and Mass Spectrometry Studies
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
Papers in
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- Bioinformatics and Genomic Networks 4
- Metabolomics and Mass Spectrometry Studies 3
- Gene expression and cancer classification 2
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- Computational Drug Discovery Methods 7
- Co-authors
- Heli Julkunen (6 shared papers)Juho Rousu (7 shared papers)Peter Würtz (5 shared papers)Tero Aittokallio (5 shared papers)Tapio Pahikkala (4 shared papers)P. Eline Slagboom (1 shared paper)Veikko Salomaa (3 shared papers)Antti J. Kangas (2 shared papers)
- Journals
- Bioinformatics (3 papers)Nature Communications (3 papers)eLife (2 papers)Nature Biotechnology (1 paper)BMC Medicine (1 paper)
- Partner nations
- FinlandUnited StatesUnited Kingdom
In The Last Decade
Anna Cichońska
16 papers receiving 914 citations
Anna Cichońska's Hit Papers
Peers
Comparison fields: 5 of 99
- Computational Theory and Mathematics 254
- Molecular Biology 428
- Genetics 154
- Biological Psychiatry 11
- Biophysics 28
Countries citing papers authored by Anna Cichońska
This map shows the geographic impact of Anna Cichońska'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 Cichońska with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Cichońska more than expected).
Fields of papers citing papers by Anna Cichońska
This network shows the impact of papers produced by Anna Cichońska. 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 Cichońska. The network helps show where Anna Cichońska may publish in the future.
Co-authors
The 25 scholars most cited alongside Anna Cichońska, 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 | Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank Hit paper breakdown → | 2023 | 260 |
| 2 | 2021 | 128 | |
| 3 | 2017 | 89 | |
| 4 | 2016 | 81 | |
| 5 | 2020 | 80 | |
| 6 | 2018 | 57 | |
| 7 | 2015 | 53 | |
| 8 | 2016 | 41 | |
| 9 | 2024 | 32 | |
| 10 | 2022 | 28 | |
| 11 | 2022 | 25 | |
| 12 | 2022 | 18 | |
| 13 | 2023 | 14 | |
| 14 | 2021 | 14 | |
| 15 | 2024 | 3 | |
| 16 | 2025 | 2 | |
| 17 | 2018 | 0 |
About Anna Cichońska
Anna Cichońska is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pharmacology, Infectious Diseases and Genetics, having authored 17 papers that have together received 925 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Bioinformatics and Genomic Networks (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Microbial Natural Products and Biosynthesis (3 papers), Gene expression and cancer classification (2 papers), Genetic Associations and Epidemiology (2 papers), Cell Image Analysis Techniques (2 papers) and COVID-19 Clinical Research Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (254 citations), Molecular Biology (428 citations), Genetics (154 citations), Biological Psychiatry (11 citations) and Biophysics (28 citations). Anna Cichońska has collaborated with scholars based in Finland, United States and United Kingdom. Frequent co-authors include Heli Julkunen, Juho Rousu, Peter Würtz, Tero Aittokallio, Tapio Pahikkala, P. Eline Slagboom, Veikko Salomaa, Antti J. Kangas, Pasi Soininen and Balaguru Ravikumar. Their work appears in journals such as Bioinformatics, Nature Communications, eLife, Nature Biotechnology and BMC Medicine.
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.