Finola E. Moore
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Cell Biology top 5%
- Zebrafish Biomedical Research Applications
Papers in
-
- CRISPR and Genetic Engineering 3
- Single-cell and spatial transcriptomics 2
- RNA Interference and Gene Delivery 2
-
- Zebrafish Biomedical Research Applications 7
- Microtubule and mitosis dynamics 2
- Co-authors
- David M. Langenau (10 shared papers)Richard I. Morimoto (1 shared paper)Heather R. Brignull (1 shared paper)Jessica S. Blackburn (5 shared papers)Sarah Martinez (3 shared papers)Riadh Lobbardi (6 shared papers)Qin Tang (5 shared papers)John C. Moore (4 shared papers)
- Journals
- The Journal of Experimental Medicine (3 papers)The Journal of Cell Biology (2 papers)Cancer Research (2 papers)Nature Methods (1 paper)Diabetes (1 paper)
- Partner nations
- United StatesBelgiumSouth Korea
In The Last Decade
Finola E. Moore
17 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 89
- Aging 123
- Cell Biology 338
- Immunology 190
- Molecular Biology 590
- Cellular and Molecular Neuroscience 116
Countries citing papers authored by Finola E. Moore
This map shows the geographic impact of Finola E. Moore'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 Finola E. Moore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Finola E. Moore more than expected).
Fields of papers citing papers by Finola E. Moore
This network shows the impact of papers produced by Finola E. Moore. 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 Finola E. Moore. The network helps show where Finola E. Moore may publish in the future.
Co-authors
The 25 scholars most cited alongside Finola E. Moore, 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 | 2006 | 180 | |
| 2 | 2000 | 163 | |
| 3 | 2012 | 140 | |
| 4 | 2014 | 121 | |
| 5 | 2014 | 90 | |
| 6 | 2017 | 59 | |
| 7 | 2016 | 58 | |
| 8 | 2016 | 57 | |
| 9 | 2008 | 53 | |
| 10 | 2018 | 48 | |
| 11 | 2007 | 31 | |
| 12 | 2010 | 19 | |
| 13 | 2012 | 10 | |
| 14 | 2020 | 5 | |
| 15 | 2019 | 1 | |
| 16 | 2022 | 1 | |
| 17 | 2023 | 1 | |
| 18 | 2016 | 0 |
About Finola E. Moore
Finola E. Moore is a scholar working on Molecular Biology, Cell Biology, Immunology, Oncology and Cancer Research, having authored 18 papers that have together received 1.0k indexed citations. Recurring topics across this work include Zebrafish Biomedical Research Applications (7 papers), Immune Cell Function and Interaction (5 papers), CAR-T cell therapy research (5 papers), CRISPR and Genetic Engineering (3 papers), Microtubule and mitosis dynamics (2 papers), Single-cell and spatial transcriptomics (2 papers), RNA Interference and Gene Delivery (2 papers) and Erythrocyte Function and Pathophysiology (2 papers). The work is most often cited by research in Aging (123 citations), Cell Biology (338 citations), Immunology (190 citations), Molecular Biology (590 citations) and Cellular and Molecular Neuroscience (116 citations). Finola E. Moore has collaborated with scholars based in United States, Belgium and South Korea. Frequent co-authors include David M. Langenau, Richard I. Morimoto, Heather R. Brignull, Jessica S. Blackburn, Sarah Martinez, Riadh Lobbardi, Qin Tang, John C. Moore, Jeffry D. Sander and Susan E. Leeman. Their work appears in journals such as The Journal of Experimental Medicine, The Journal of Cell Biology, Cancer Research, Nature Methods and Diabetes.
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.