Michaela Fellner
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
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- Neurobiology and Insect Physiology Research
Papers in
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- Protein Degradation and Inhibitors 5
- CRISPR and Genetic Engineering 5
- Advanced biosensing and bioanalysis techniques 4
- RNA and protein synthesis mechanisms 3
- RNA Interference and Gene Delivery 3
- Histone Deacetylase Inhibitors Research 2
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- Acute Myeloid Leukemia Research 4
- Co-authors
- Barry J. Dickson (3 shared papers)Frank Schnorrer (3 shared papers)Georg Dietzl (2 shared papers)Krystyna Keleman (2 shared papers)Doris Chen (3 shared papers)Kuan-Chung Su (1 shared paper)Africa Couto (1 shared paper)Johannes Zuber (12 shared papers)
- Journals
- Nature Chemical Biology (2 papers)Blood (2 papers)Nature (2 papers)eLife (2 papers)Nature Methods (2 papers)
- Partner nations
- AustriaGermanyNetherlands
In The Last Decade
Michaela Fellner
15 papers receiving 2.9k citations
Michaela Fellner's Hit Papers
Peers
Comparison fields: 5 of 96
- Aging 240
- Cellular and Molecular Neuroscience 1.1k
- Cell Biology 523
- Molecular Biology 1.9k
- Immunology 407
Countries citing papers authored by Michaela Fellner
This map shows the geographic impact of Michaela Fellner'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 Michaela Fellner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michaela Fellner more than expected).
Fields of papers citing papers by Michaela Fellner
This network shows the impact of papers produced by Michaela Fellner. 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 Michaela Fellner. The network helps show where Michaela Fellner may publish in the future.
Co-authors
The 25 scholars most cited alongside Michaela Fellner, 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 | A genome-wide transgenic RNAi library for conditional gene inactivation in Drosophila Hit paper breakdown → | 2007 | 2139 |
| 2 | 2020 | 267 | |
| 3 | 2010 | 223 | |
| 4 | 2020 | 91 | |
| 5 | 2020 | 64 | |
| 6 | 2008 | 44 | |
| 7 | 2021 | 31 | |
| 8 | 2022 | 21 | |
| 9 | 2021 | 16 | |
| 10 | 2008 | 12 | |
| 11 | 2021 | 5 | |
| 12 | 2022 | 4 | |
| 13 | 2023 | 3 | |
| 14 | 2023 | 1 | |
| 15 | 2022 | 1 | |
| 16 | 2024 | 0 |
About Michaela Fellner
Michaela Fellner is a scholar working on Molecular Biology, Hematology, Immunology, Cellular and Molecular Neuroscience and Organic Chemistry, having authored 16 papers that have together received 2.9k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (5 papers), CRISPR and Genetic Engineering (5 papers), Acute Myeloid Leukemia Research (4 papers), Advanced biosensing and bioanalysis techniques (4 papers), RNA and protein synthesis mechanisms (3 papers), RNA Interference and Gene Delivery (3 papers), Histone Deacetylase Inhibitors Research (2 papers) and Neurobiology and Insect Physiology Research (2 papers). The work is most often cited by research in Aging (240 citations), Cellular and Molecular Neuroscience (1.1k citations), Cell Biology (523 citations), Molecular Biology (1.9k citations) and Immunology (407 citations). Michaela Fellner has collaborated with scholars based in Austria, Germany and Netherlands. Frequent co-authors include Barry J. Dickson, Frank Schnorrer, Georg Dietzl, Krystyna Keleman, Doris Chen, Kuan-Chung Su, Africa Couto, Johannes Zuber, Alexander Stark and Maria Novatchkova. Their work appears in journals such as Nature Chemical Biology, Blood, Nature, eLife and Nature Methods.
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.