Magnus Ekeberg
Impact in
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- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- Microbial Metabolic Engineering and Bioproduction
Papers in
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- Protein Structure and Dynamics 4
- Machine Learning in Bioinformatics 1
- RNA and protein synthesis mechanisms 1
- Genomics and Phylogenetic Studies 1
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- Theoretical and Computational Physics 1
- Co-authors
- Erik Aurell (3 shared papers)Martin Weigt (1 shared paper)Yueheng Lan (1 shared paper)Cecilia Lövkvist (1 shared paper)Tuomo Hartonen (1 shared paper)Mirco Michel (1 shared paper)Marcin J. Skwark (1 shared paper)David Menéndez Hurtado (1 shared paper)
- Journals
- Bioinformatics (1 paper)Physical Review Letters (1 paper)Journal of Computational Physics (1 paper)Physical Review E (1 paper)
In The Last Decade
Magnus Ekeberg
4 papers receiving 674 citations
Magnus Ekeberg's Hit Papers
Peers
Comparison fields: 5 of 69
- Molecular Biology 560
- Acoustics and Ultrasonics 4
- Statistical and Nonlinear Physics 52
- Genetics 114
- Statistics and Probability 31
Countries citing papers authored by Magnus Ekeberg
This map shows the geographic impact of Magnus Ekeberg'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 Magnus Ekeberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Magnus Ekeberg more than expected).
Fields of papers citing papers by Magnus Ekeberg
This network shows the impact of papers produced by Magnus Ekeberg. 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 Magnus Ekeberg. The network helps show where Magnus Ekeberg may publish in the future.
Co-authors
The 9 scholars most cited alongside Magnus Ekeberg, 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 | Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models Hit paper breakdown → | 2013 | 438 |
| 2 | 2014 | 116 | |
| 3 | 2012 | 98 | |
| 4 | 2017 | 30 |
About Magnus Ekeberg
Magnus Ekeberg is a scholar working on Molecular Biology, Condensed Matter Physics, Information Systems, Statistical and Nonlinear Physics and Atomic and Molecular Physics, and Optics, having authored 4 papers that have together received 682 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (4 papers), Complex Network Analysis Techniques (1 paper), Machine Learning in Bioinformatics (1 paper), Software Engineering Research (1 paper), Theoretical and Computational Physics (1 paper), RNA and protein synthesis mechanisms (1 paper), Spectroscopy and Quantum Chemical Studies (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Molecular Biology (560 citations), Acoustics and Ultrasonics (4 citations), Statistical and Nonlinear Physics (52 citations), Genetics (114 citations) and Statistics and Probability (31 citations). Magnus Ekeberg has collaborated with scholars based in Sweden, Finland and France. Frequent co-authors include Erik Aurell, Martin Weigt, Yueheng Lan, Cecilia Lövkvist, Tuomo Hartonen, Mirco Michel, Marcin J. Skwark, David Menéndez Hurtado and Arne Elofsson. Their work appears in journals such as Bioinformatics, Physical Review Letters, Journal of Computational Physics and Physical Review E.
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.