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
- Machine Learning in Bioinformatics 1
- RNA and protein synthesis mechanisms 1
- Co-authors
- Wolfgang G. Müller (6 shared papers)Ulrike Wittig (7 shared papers)Andreas Weidemann (6 shared papers)Renate Kania (4 shared papers)Meik Bittkowski (3 shared papers)Lei Shi (3 shared papers)Isabel Rojas (3 shared papers)Martin Golebiewski (3 shared papers)
- Journals
- Nucleic Acids Research (2 papers)Journal of Biotechnology (1 paper)Computers & Chemical Engineering (1 paper)Journal of The Royal Society Interface (1 paper)Electrochimica Acta (1 paper)
- Partner nations
- GermanyUnited Kingdom
In The Last Decade
Maja Rey
9 papers receiving 381 citations
Peers
Comparison fields: 5 of 70
- Molecular Biology 309
- Information Systems and Management 24
- Computational Theory and Mathematics 36
- Modeling and Simulation 7
- Filtration and Separation 3
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 | 181 | |
| 2 | 2017 | 110 | |
| 3 | 1961 | 24 | |
| 4 | 2011 | 19 | |
| 5 | 2006 | 19 | |
| 6 | 2014 | 14 | |
| 7 | 2013 | 13 | |
| 8 | 2017 | 6 | |
| 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 387 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), Machine Learning in Bioinformatics (1 paper), Gas Sensing Nanomaterials and Sensors (1 paper), Diet, Metabolism, and Disease (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Molecular Biology (309 citations), Information Systems and Management (24 citations), Computational Theory and Mathematics (36 citations), Modeling and Simulation (7 citations) and Filtration and Separation (3 citations). Maja Rey has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Wolfgang G. Müller, Ulrike Wittig, Andreas Weidemann, Renate Kania, Meik Bittkowski, Lei Shi, Isabel Rojas, Martin Golebiewski, Lenneke M. Jong and Oliver Krebs. Their work appears in journals such as Nucleic Acids Research, Journal of Biotechnology, Computers & Chemical Engineering, Journal of The Royal Society Interface and Electrochimica Acta.
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.