Martin Pačesa
Impact in
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- Innovation and Socioeconomic Development
Papers in
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- CRISPR and Genetic Engineering 4
- RNA and protein synthesis mechanisms 4
- DNA Repair Mechanisms 3
- Protein Structure and Dynamics 2
- Advanced biosensing and bioanalysis techniques 2
- Receptor Mechanisms and Signaling 1
- Oncology 3
- PARP inhibition in cancer therapy 1
- Co-authors
- Martin Jínek (3 shared papers)Marta Sawicka (1 shared paper)Irma Querques (1 shared paper)Lena M. Muckenfuss (1 shared paper)Luuk Loeff (1 shared paper)Bruno E. Correia (3 shared papers)Sandrine Georgeon (3 shared papers)Marek Šebesta (3 shared papers)
- Journals
- Nature (4 papers)Nucleic Acids Research (3 papers)Molecular Cell (2 papers)Virology Journal (1 paper)Cell (1 paper)
- Partner nations
- SwitzerlandUnited StatesUnited Kingdom
In The Last Decade
Martin Pačesa
12 papers receiving 539 citations
Martin Pačesa's Hit Papers
Peers
Comparison fields: 5 of 66
- Business and International Management 27
- Aging 18
- Molecular Biology 414
- Genetics 95
- Structural Biology 5
Countries citing papers authored by Martin Pačesa
This map shows the geographic impact of Martin Pačesa'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 Martin Pačesa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Pačesa more than expected).
Fields of papers citing papers by Martin Pačesa
This network shows the impact of papers produced by Martin Pačesa. 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 Martin Pačesa. The network helps show where Martin Pačesa may publish in the future.
Co-authors
The 25 scholars most cited alongside Martin Pačesa, 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 | 2022 | 104 | |
| 2 | 2024 | 66 | |
| 3 | 2018 | 60 | |
| 4 | Computational design of soluble and functional membrane protein analogues Hit paper breakdown → | 2024 | 58 |
| 5 | 2021 | 46 | |
| 6 | 2022 | 45 | |
| 7 | Design of highly functional genome editors by modelling CRISPR–Cas sequences Hit paper breakdown → | 2025 | 37 |
| 8 | 2017 | 36 | |
| 9 | 2016 | 32 | |
| 10 | Targeting protein–ligand neosurfaces with a generalizable deep learning tool Hit paper breakdown → | 2025 | 28 |
| 11 | 2016 | 21 | |
| 12 | 2017 | 10 | |
| 13 | 2026 | 0 |
About Martin Pačesa
Martin Pačesa is a scholar working on Molecular Biology, Oncology, Genetics, Business and International Management and Computational Theory and Mathematics, having authored 13 papers that have together received 543 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), RNA and protein synthesis mechanisms (4 papers), DNA Repair Mechanisms (3 papers), Protein Structure and Dynamics (2 papers), Advanced biosensing and bioanalysis techniques (2 papers), Virus-based gene therapy research (2 papers), Receptor Mechanisms and Signaling (1 paper) and PARP inhibition in cancer therapy (1 paper). The work is most often cited by research in Business and International Management (27 citations), Aging (18 citations), Molecular Biology (414 citations), Genetics (95 citations) and Structural Biology (5 citations). Martin Pačesa has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include Martin Jínek, Marta Sawicka, Irma Querques, Lena M. Muckenfuss, Luuk Loeff, Bruno E. Correia, Sandrine Georgeon, Marek Šebesta, Lumír Krejčí and Casper A. Goverde. Their work appears in journals such as Nature, Nucleic Acids Research, Molecular Cell, Virology Journal and Cell.
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.