Mareike D. Hoffmann
Impact in
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- Innovation and Socioeconomic Development
- Biochemistry top 5%
- Lipid metabolism and biosynthesis
Papers in ⓘ
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- CRISPR and Genetic Engineering 9
- RNA and protein synthesis mechanisms 4
- Advanced biosensing and bioanalysis techniques 3
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- Photoreceptor and optogenetics research 3
- Co-authors
- Dominik Niopek (9 shared papers)Roland Eils (7 shared papers)Sabine Aschenbrenner (5 shared papers)Dirk Grimm (4 shared papers)Ivo Feußner (2 shared papers)Kathleen Börner (2 shared papers)Julia Fakhiri (2 shared papers)Felix Bubeck (4 shared papers)
- Journals
- Journal of Biological Chemistry (2 papers)Nucleic Acids Research (2 papers)Nature Methods (1 paper)Physical Review B (1 paper)Nature Machine Intelligence (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Mareike D. Hoffmann
20 papers receiving 766 citations
Peers
Comparison fields: 5 of 87
- Business and International Management 65
- Biochemistry 87
- Aging 19
- Molecular Biology 541
- Immunology 103
Countries citing papers authored by Mareike D. Hoffmann
This map shows the geographic impact of Mareike D. Hoffmann'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 Mareike D. Hoffmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mareike D. Hoffmann more than expected).
Fields of papers citing papers by Mareike D. Hoffmann
This network shows the impact of papers produced by Mareike D. Hoffmann. 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 Mareike D. Hoffmann. The network helps show where Mareike D. Hoffmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Mareike D. Hoffmann, 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 | 2018 | 158 | |
| 2 | 2012 | 97 | |
| 3 | 2019 | 85 | |
| 4 | 2008 | 81 | |
| 5 | 1985 | 64 | |
| 6 | 2012 | 48 | |
| 7 | 2020 | 46 | |
| 8 | 2008 | 46 | |
| 9 | 2020 | 33 | |
| 10 | 2007 | 33 | |
| 11 | 2018 | 22 | |
| 12 | 2019 | 19 | |
| 13 | 2020 | 15 | |
| 14 | 2020 | 14 | |
| 15 | 2023 | 8 | |
| 16 | 2024 | 6 | |
| 17 | 2017 | 6 | |
| 18 | 2025 | 2 | |
| 19 | 2022 | 1 | |
| 20 | 2020 | 1 |
About Mareike D. Hoffmann
Mareike D. Hoffmann is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Biochemistry and Cardiology and Cardiovascular Medicine, having authored 20 papers that have together received 785 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (9 papers), RNA and protein synthesis mechanisms (4 papers), Advanced biosensing and bioanalysis techniques (3 papers), Lipid metabolism and biosynthesis (3 papers), Photoreceptor and optogenetics research (3 papers), Innovation and Socioeconomic Development (2 papers), Virus-based gene therapy research (2 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Business and International Management (65 citations), Biochemistry (87 citations), Aging (19 citations), Molecular Biology (541 citations) and Immunology (103 citations). Mareike D. Hoffmann has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Dominik Niopek, Roland Eils, Sabine Aschenbrenner, Dirk Grimm, Ivo Feußner, Kathleen Börner, Julia Fakhiri, Felix Bubeck, Martin Wagner and Zander Harteveld. Their work appears in journals such as Journal of Biological Chemistry, Nucleic Acids Research, Nature Methods, Physical Review B and Nature Machine Intelligence.
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.