Norbert Perrimon
Impact in
- Aging top 0.01%
- Genetics, Aging, and Longevity in Model Organisms
- Cell Biology top 0.01%
- Hippo pathway signaling and YAP/TAZ
Papers in
- Aging 71
- Genetics, Aging, and Longevity in Model Organisms 71
- Cell Biology 110
- Hippo pathway signaling and YAP/TAZ 53
- Co-authors
- Andrea H. BrandTze-Bin ChouDavid BilderAnthony P. MahowaldStephanie E. MohrMichael BoutrosCraig A. MicchelliFabio Demontis
- Journals
- Proceedings of the National Academy of Sciences (42 papers)Development (40 papers)Genetics (32 papers)Developmental Biology (27 papers)Nature (26 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Norbert Perrimon
545 papers receiving 62.1k citations
Hit Papers
Peers
Comparison fields: 5 of 198
- Aging 4.1k
- Cell Biology 14.9k
- Cellular and Molecular Neuroscience 13.3k
- Molecular Biology 44.0k
- Immunology 10.2k
Countries citing papers authored by Norbert Perrimon
This map shows the geographic impact of Norbert Perrimon'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 Norbert Perrimon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Norbert Perrimon more than expected).
Fields of papers citing papers by Norbert Perrimon
This network shows the impact of papers produced by Norbert Perrimon. 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 Norbert Perrimon. The network helps show where Norbert Perrimon may publish in the future.
Co-authors
The 25 scholars most cited alongside Norbert Perrimon, 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 | 2022 | 17 | |
| 2 | 2020 | 10 | |
| 3 | 2020 | 7 | |
| 4 | 2020 | 71 | |
| 5 | 2020 | 162 | |
| 6 | 2019 | 29 | |
| 7 | 2019 | 38 | |
| 8 | 2018 | 44 | |
| 9 | 2018 | 23 | |
| 10 | 2017 | 5 | |
| 11 | 2017 | 14 | |
| 12 | 2016 | 34 | |
| 13 | 2015 | 117 | |
| 14 | 2013 | 65 | |
| 15 | 2008 | 9 | |
| 16 | 2008 | 98 | |
| 17 | 2008 | 55 | |
| 18 | 2005 | 238 | |
| 19 | 2005 | 153 | |
| 20 | 2003 | 139 |
About Norbert Perrimon
Norbert Perrimon is a scholar working on Aging, Cell Biology, Molecular Biology, Cellular and Molecular Neuroscience and Immunology, having authored 556 papers that have together received 62.9k indexed citations. Recurring topics across this work include Developmental Biology and Gene Regulation (134 papers), Neurobiology and Insect Physiology Research (97 papers), CRISPR and Genetic Engineering (93 papers), Invertebrate Immune Response Mechanisms (82 papers), Genetics, Aging, and Longevity in Model Organisms (71 papers), Hippo pathway signaling and YAP/TAZ (53 papers), Wnt/β-catenin signaling in development and cancer (52 papers) and RNA Research and Splicing (40 papers). The work is most often cited by research in Aging (4.1k citations), Cell Biology (14.9k citations), Cellular and Molecular Neuroscience (13.3k citations), Molecular Biology (44.0k citations) and Immunology (10.2k citations). Norbert Perrimon has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Andrea H. Brand, Tze-Bin Chou, David Bilder, Anthony P. Mahowald, Stephanie E. Mohr, Michael Boutros, Craig A. Micchelli, Fabio Demontis, Xinhua Lin and Richard Binari. Their work appears in journals such as Proceedings of the National Academy of Sciences, Development, Genetics, Developmental Biology and Nature.
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.