Witold Dyrka
Impact in
Papers in
-
- Machine Learning in Bioinformatics 4
- Prion Diseases and Protein Misfolding 2
- Protein Structure and Dynamics 2
- RNA and protein synthesis mechanisms 2
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- Plant-Microbe Interactions and Immunity 3
- Co-authors
- Sven J. Saupe (5 shared papers)Asen Daskalov (4 shared papers)Jean‐Christophe Nebel (4 shared papers)David James Sherman (1 shared paper)Boštjan Kobe (1 shared paper)Pascal Durrens (1 shared paper)Małgorzata Kotulska (5 shared papers)Sven J. Saupe (1 shared paper)
- Journals
- BMC Bioinformatics (3 papers)Journal of Molecular Biology (1 paper)Scientific Reports (1 paper)BMC Systems Biology (1 paper)Journal of Computational Chemistry (1 paper)
- Partner nations
- PolandFranceUnited Kingdom
In The Last Decade
Witold Dyrka
15 papers receiving 255 citations
Peers
Comparison fields: 5 of 59
- Endocrinology 22
- Parasitology 18
- Plant Science 89
- Molecular Biology 151
- Immunology 36
Countries citing papers authored by Witold Dyrka
This map shows the geographic impact of Witold Dyrka'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 Witold Dyrka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Witold Dyrka more than expected).
Fields of papers citing papers by Witold Dyrka
This network shows the impact of papers produced by Witold Dyrka. 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 Witold Dyrka. The network helps show where Witold Dyrka may publish in the future.
Co-authors
The 25 scholars most cited alongside Witold Dyrka, 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 | 2014 | 80 | |
| 2 | 2022 | 41 | |
| 3 | 2015 | 22 | |
| 4 | 2009 | 21 | |
| 5 | 2020 | 20 | |
| 6 | 2016 | 20 | |
| 7 | 2008 | 16 | |
| 8 | 2022 | 12 | |
| 9 | 2013 | 9 | |
| 10 | 2017 | 6 | |
| 11 | 2019 | 4 | |
| 12 | 2007 | 3 | |
| 13 | 2021 | 2 | |
| 14 | 2013 | 1 | |
| 15 | Probabilistic grammatical model of protein language and its application to helix-helix contact site classification | 2013 | 1 |
| 16 | 2024 | 0 |
About Witold Dyrka
Witold Dyrka is a scholar working on Molecular Biology, Plant Science, Cell Biology, Physiology and Biomedical Engineering, having authored 16 papers that have together received 258 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (4 papers), Plant-Microbe Interactions and Immunity (3 papers), Alzheimer's disease research and treatments (2 papers), Prion Diseases and Protein Misfolding (2 papers), Protein Structure and Dynamics (2 papers), Nanopore and Nanochannel Transport Studies (2 papers), RNA and protein synthesis mechanisms (2 papers) and Mass Spectrometry Techniques and Applications (1 paper). The work is most often cited by research in Endocrinology (22 citations), Parasitology (18 citations), Plant Science (89 citations), Molecular Biology (151 citations) and Immunology (36 citations). Witold Dyrka has collaborated with scholars based in Poland, France and United Kingdom. Frequent co-authors include Sven J. Saupe, Asen Daskalov, Jean‐Christophe Nebel, David James Sherman, Boštjan Kobe, Pascal Durrens, Małgorzata Kotulska, Sven J. Saupe, A.T. Augousti and Benoı̂t Pinson. Their work appears in journals such as BMC Bioinformatics, Journal of Molecular Biology, Scientific Reports, BMC Systems Biology and Journal of Computational Chemistry.
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.