László Kaján
Impact in
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- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- Microbial Metabolic Engineering and Bioproduction
Papers in
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- Machine Learning in Bioinformatics 5
- Genomics and Phylogenetic Studies 4
- Protein Structure and Dynamics 3
- RNA and protein synthesis mechanisms 2
- Bioinformatics and Genomic Networks 2
- Porphyrin Metabolism and Disorders 1
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- Scientific Computing and Data Management 2
- Co-authors
- Burkhard Rost (4 shared papers)Guy Yachdav (3 shared papers)Avner Schlessinger (2 shared papers)Marco Punta (2 shared papers)Matúš Kalaš (2 shared papers)Lothar Richter (1 shared paper)Debora S. Marks (1 shared paper)Chris Sander (1 shared paper)
- Journals
- Bioinformatics (3 papers)BMC Bioinformatics (3 papers)Polymer (1 paper)Biochemistry (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- HungaryUnited StatesGermany
In The Last Decade
László Kaján
12 papers receiving 946 citations
László Kaján's Hit Papers
Peers
Comparison fields: 5 of 108
- Molecular Biology 640
- Clinical Biochemistry 32
- Endocrinology 19
- Biochemistry 27
- Cell Biology 58
Countries citing papers authored by László Kaján
This map shows the geographic impact of László Kaján'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 Kaján with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites László Kaján more than expected).
Fields of papers citing papers by László Kaján
This network shows the impact of papers produced by László Kaján. 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 Kaján. The network helps show where László Kaján may publish in the future.
Co-authors
The 25 scholars most cited alongside László Kaján, 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 | PredictProtein—an open resource for online prediction of protein structural and functional features Hit paper breakdown → | 2014 | 475 |
| 2 | 2009 | 156 | |
| 3 | 2014 | 122 | |
| 4 | 2007 | 58 | |
| 5 | 2005 | 57 | |
| 6 | 2007 | 32 | |
| 7 | 2006 | 20 | |
| 8 | 2007 | 17 | |
| 9 | 2013 | 11 | |
| 10 | 2005 | 9 | |
| 11 | 2003 | 2 | |
| 12 | 2013 | 2 |
About László Kaján
László Kaján is a scholar working on Molecular Biology, Information Systems and Management, Clinical Biochemistry, Artificial Intelligence and Rheumatology, having authored 12 papers that have together received 961 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (5 papers), Genomics and Phylogenetic Studies (4 papers), Protein Structure and Dynamics (3 papers), Scientific Computing and Data Management (2 papers), RNA and protein synthesis mechanisms (2 papers), Bioinformatics and Genomic Networks (2 papers), Folate and B Vitamins Research (1 paper) and Porphyrin Metabolism and Disorders (1 paper). The work is most often cited by research in Molecular Biology (640 citations), Clinical Biochemistry (32 citations), Endocrinology (19 citations), Biochemistry (27 citations) and Cell Biology (58 citations). László Kaján has collaborated with scholars based in Hungary, United States and Germany. Frequent co-authors include Burkhard Rost, Guy Yachdav, Avner Schlessinger, Marco Punta, Matúš Kalaš, Lothar Richter, Debora S. Marks, Chris Sander, Peter Hönigschmid and Tobias Hamp. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, Polymer, Biochemistry and Nucleic Acids Research.
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.