Maja Rey
Impact in
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- Microbial Metabolic Engineering and Bioproduction
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Enzyme Catalysis and Immobilization
- Protein Structure and Dynamics
- Metabolomics and Mass Spectrometry Studies
Papers in
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- Bioinformatics and Genomic Networks 6
- Microbial Metabolic Engineering and Bioproduction 5
- Gene Regulatory Network Analysis 4
- Biomedical Text Mining and Ontologies 2
- Mitochondrial Function and Pathology 1
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- Web Data Mining and Analysis 1
- Co-authors
- Andreas Weidemann (6 shared papers)Ulrike Wittig (7 shared papers)Wolfgang G. Müller (6 shared papers)Renate Kania (4 shared papers)Lei Shi (3 shared papers)Martin Golebiewski (3 shared papers)Meik Bittkowski (3 shared papers)Isabel Rojas (3 shared papers)
- Journals
- Nucleic Acids Research (2 papers)Journal of The Royal Society Interface (1 paper)Database (1 paper)FEBS Journal (1 paper)Computers & Chemical Engineering (1 paper)
- Partner nations
- GermanyUnited Kingdom
In The Last Decade
Maja Rey
9 papers receiving 415 citations
Peers
Comparison fields: 5 of 71
- Molecular Biology 312
- Information Systems and Management 27
- Computational Theory and Mathematics 34
- Filtration and Separation 3
- Modeling and Simulation 6
Countries citing papers authored by Maja Rey
This map shows the geographic impact of Maja Rey'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 Maja Rey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maja Rey more than expected).
Fields of papers citing papers by Maja Rey
This network shows the impact of papers produced by Maja Rey. 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 Maja Rey. The network helps show where Maja Rey may publish in the future.
Co-authors
The 24 scholars most cited alongside Maja Rey, 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 | 2011 | 198 | |
| 2 | 2017 | 119 | |
| 3 | 1961 | 25 | |
| 4 | 2006 | 21 | |
| 5 | 2011 | 20 | |
| 6 | 2013 | 15 | |
| 7 | 2014 | 14 | |
| 8 | 2017 | 8 | |
| 9 | 2023 | 1 | |
| 10 | 2020 | 0 |
About Maja Rey
Maja Rey is a scholar working on Molecular Biology, Information Systems, Information Systems and Management, Artificial Intelligence and Endocrinology, Diabetes and Metabolism, having authored 10 papers that have together received 421 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (6 papers), Microbial Metabolic Engineering and Bioproduction (5 papers), Gene Regulatory Network Analysis (4 papers), Biomedical Text Mining and Ontologies (2 papers), Analytical Chemistry and Sensors (1 paper), Web Data Mining and Analysis (1 paper), Mitochondrial Function and Pathology (1 paper) and Diet, Metabolism, and Disease (1 paper). The work is most often cited by research in Molecular Biology (312 citations), Information Systems and Management (27 citations), Computational Theory and Mathematics (34 citations), Filtration and Separation (3 citations) and Modeling and Simulation (6 citations). Maja Rey has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Andreas Weidemann, Ulrike Wittig, Wolfgang G. Müller, Renate Kania, Lei Shi, Martin Golebiewski, Meik Bittkowski, Isabel Rojas, Lenneke M. Jong and Oliver Krebs. Their work appears in journals such as Nucleic Acids Research, Journal of The Royal Society Interface, Database, FEBS Journal and Computers & Chemical Engineering.
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.