Richard Binari
Impact in
- Aging top 0.5%
- Genetics, Aging, and Longevity in Model Organisms
-
- Neurobiology and Insect Physiology Research
Papers in
- Aging 6
- Genetics, Aging, and Longevity in Model Organisms 6
-
- CRISPR and Genetic Engineering 7
- RNA Research and Splicing 5
- Developmental Biology and Gene Regulation 5
- Co-authors
- Norbert PerrimonDouglas A. HarrisonMichael GilmanLizabeth A. PerkinsArmen S. ManoukianRui ZhouMatthew A. BookerTheresa Stines Nahreini
- Journals
- Proceedings of the National Academy of Sciences (5 papers)Developmental Cell (4 papers)Nature Methods (3 papers)Genes & Development (3 papers)eLife (3 papers)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Richard Binari
40 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Aging 305
- Cellular and Molecular Neuroscience 1.1k
- Immunology 1.1k
- Molecular Biology 3.0k
- Cell Biology 691
Countries citing papers authored by Richard Binari
This map shows the geographic impact of Richard Binari'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 Richard Binari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Binari more than expected).
Fields of papers citing papers by Richard Binari
This network shows the impact of papers produced by Richard Binari. 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 Richard Binari. The network helps show where Richard Binari may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Richard Binari, 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 | 2023 | 9 | |
| 2 | 2022 | 25 | |
| 3 | 2022 | 9 | |
| 4 | 2021 | 7 | |
| 5 | 2021 | 53 | |
| 6 | 2020 | 34 | |
| 7 | 2019 | 51 | |
| 8 | 2019 | 57 | |
| 9 | 2016 | 16 | |
| 10 | 2015 | 58 | |
| 11 | 2014 | 50 | |
| 12 | 2014 | 104 | |
| 13 | A genome-scale shRNA resource for transgenic RNAi in Drosophila Hit paper breakdown → | 2011 | 605 |
| 14 | 2011 | 71 | |
| 15 | 2009 | 205 | |
| 16 | 2009 | 48 | |
| 17 | 2008 | 55 | |
| 18 | 2007 | 219 | |
| 19 | 2005 | 473 | |
| 20 | 2002 | 78 |
About Richard Binari
Richard Binari is a scholar working on Aging, Molecular Biology, Cellular and Molecular Neuroscience, Immunology and Cell Biology, having authored 40 papers that have together received 4.5k indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (7 papers), CRISPR and Genetic Engineering (7 papers), Genetics, Aging, and Longevity in Model Organisms (6 papers), Hippo pathway signaling and YAP/TAZ (5 papers), RNA Research and Splicing (5 papers), Developmental Biology and Gene Regulation (5 papers), Invertebrate Immune Response Mechanisms (4 papers) and Virus-based gene therapy research (3 papers). The work is most often cited by research in Aging (305 citations), Cellular and Molecular Neuroscience (1.1k citations), Immunology (1.1k citations), Molecular Biology (3.0k citations) and Cell Biology (691 citations). Richard Binari has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Norbert Perrimon, Douglas A. Harrison, Michael Gilman, Lizabeth A. Perkins, Armen S. Manoukian, Rui Zhou, Matthew A. Booker, Theresa Stines Nahreini, Christians Villalta and Jian-Quan Ni. Their work appears in journals such as Proceedings of the National Academy of Sciences, Developmental Cell, Nature Methods, Genes & Development and eLife.
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.