László Dobson
Impact in
- Molecular Biology top 10%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- RNA Research and Splicing
- Bioinformatics and Genomic Networks
Papers in
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- Machine Learning in Bioinformatics 17
- RNA and protein synthesis mechanisms 16
- Protein Structure and Dynamics 10
- Bioinformatics and Genomic Networks 3
- RNA Research and Splicing 3
- Glycosylation and Glycoproteins Research 2
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- Advanced Proteomics Techniques and Applications 4
- Co-authors
- Gábor Tusnády (18 shared papers)István Reményi (4 shared papers)András Zeke (7 shared papers)Bálint Mészáros (7 shared papers)Nazanin Farahi (2 shared papers)Lucía B. Chemes (2 shared papers)Rita Pancsa (3 shared papers)Norman E. Davey (2 shared papers)
In The Last Decade
László Dobson
27 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 781
- Cell Biology 78
- Spectroscopy 80
- Biochemistry 34
- Parasitology 23
Countries citing papers authored by László Dobson
This map shows the geographic impact of László Dobson'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 László Dobson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites László Dobson more than expected).
Fields of papers citing papers by László Dobson
This network shows the impact of papers produced by László Dobson. 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 László Dobson. The network helps show where László Dobson may publish in the future.
Co-authors
The 25 scholars most cited alongside László Dobson, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 320 | |
| 2 | 2021 | 163 | |
| 3 | 2021 | 119 | |
| 4 | 2015 | 99 | |
| 5 | 2020 | 79 | |
| 6 | 2022 | 55 | |
| 7 | 2014 | 35 | |
| 8 | 2015 | 24 | |
| 9 | 2017 | 15 | |
| 10 | 2023 | 15 | |
| 11 | 2016 | 14 | |
| 12 | 2023 | 14 | |
| 13 | 2021 | 13 | |
| 14 | 2015 | 12 | |
| 15 | 2019 | 12 | |
| 16 | 2018 | 8 | |
| 17 | 2022 | 5 | |
| 18 | 2020 | 5 | |
| 19 | 2020 | 5 | |
| 20 | 2019 | 4 |
About László Dobson
László Dobson is a scholar working on Molecular Biology, Spectroscopy, Materials Chemistry, Epidemiology and Public Health, Environmental and Occupational Health, having authored 27 papers that have together received 1.0k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (17 papers), RNA and protein synthesis mechanisms (16 papers), Protein Structure and Dynamics (10 papers), Advanced Proteomics Techniques and Applications (4 papers), Enzyme Structure and Function (3 papers), Bioinformatics and Genomic Networks (3 papers), RNA Research and Splicing (3 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Molecular Biology (781 citations), Cell Biology (78 citations), Spectroscopy (80 citations), Biochemistry (34 citations) and Parasitology (23 citations). László Dobson has collaborated with scholars based in Hungary, Germany and Belgium. Frequent co-authors include Gábor Tusnády, István Reményi, András Zeke, Bálint Mészáros, Nazanin Farahi, Lucía B. Chemes, Rita Pancsa, Norman E. Davey, Tamás Lázár and Toby J. Gibson. Their work appears in journals such as Nucleic Acids Research, Scientific Reports, Journal of Molecular Biology, Bioinformatics and Database.
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.