Matej Lexa
Impact in
- Molecular Biology top 10%
- RNA and protein synthesis mechanisms
- DNA and Nucleic Acid Chemistry
- Advanced biosensing and bioanalysis techniques
- Genomics and Phylogenetic Studies
- Gut microbiota and health
- Plant Science top 10%
- Chromosomal and Genetic Variations
- Plant Molecular Biology Research
- Plant Virus Research Studies
Papers in
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- Genomics and Phylogenetic Studies 7
- RNA and protein synthesis mechanisms 6
-
- Chromosomal and Genetic Variations 14
- Plant Virus Research Studies 7
- Plant nutrient uptake and metabolism 5
- Plant Molecular Biology Research 5
- Plant Disease Resistance and Genetics 3
- Co-authors
- Eduard Kejnovský (13 shared papers)Tomáš Martínek (8 shared papers)Jiří Hon (3 shared papers)Jaroslav Zendulka (1 shared paper)Giorgio Valle (2 shared papers)Pavel Jedlička (7 shared papers)Boris Vyskot (3 shared papers)John M. Cheeseman (2 shared papers)
In The Last Decade
Matej Lexa
43 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 102
- Molecular Biology 700
- Plant Science 345
- Horticulture 5
- Agronomy and Crop Science 42
- Ecology 97
Countries citing papers authored by Matej Lexa
This map shows the geographic impact of Matej Lexa'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 Matej Lexa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matej Lexa more than expected).
Fields of papers citing papers by Matej Lexa
This network shows the impact of papers produced by Matej Lexa. 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 Matej Lexa. The network helps show where Matej Lexa may publish in the future.
Co-authors
The 25 scholars most cited alongside Matej Lexa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 142 | |
| 2 | 2019 | 81 | |
| 3 | 2013 | 53 | |
| 4 | 2016 | 48 | |
| 5 | 2013 | 42 | |
| 6 | 2015 | 38 | |
| 7 | 2019 | 37 | |
| 8 | 2015 | 36 | |
| 9 | 2003 | 36 | |
| 10 | 2004 | 35 | |
| 11 | 2014 | 35 | |
| 12 | 2013 | 31 | |
| 13 | 2013 | 31 | |
| 14 | 2020 | 31 | |
| 15 | 2011 | 27 | |
| 16 | 2003 | 27 | |
| 17 | 2001 | 26 | |
| 18 | 2013 | 25 | |
| 19 | 2016 | 24 | |
| 20 | 2019 | 23 |
About Matej Lexa
Matej Lexa is a scholar working on Molecular Biology, Plant Science, Artificial Intelligence, Genetics and Infectious Diseases, having authored 46 papers that have together received 1.1k indexed citations. Recurring topics across this work include Chromosomal and Genetic Variations (14 papers), Genomics and Phylogenetic Studies (7 papers), Plant Virus Research Studies (7 papers), RNA and protein synthesis mechanisms (6 papers), Plant nutrient uptake and metabolism (5 papers), Plant Molecular Biology Research (5 papers), Plant Disease Resistance and Genetics (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Molecular Biology (700 citations), Plant Science (345 citations), Horticulture (5 citations), Agronomy and Crop Science (42 citations) and Ecology (97 citations). Matej Lexa has collaborated with scholars based in Czechia, Germany and Bulgaria. Frequent co-authors include Eduard Kejnovský, Tomáš Martínek, Jiří Hon, Jaroslav Zendulka, Giorgio Valle, Pavel Jedlička, Boris Vyskot, John M. Cheeseman, David Šmajs and Juraj Bosák. Their work appears in journals such as Bioinformatics, PLoS ONE, Briefings in Bioinformatics, BMC Genomics and Frontiers in Immunology.
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.