Gai Ayalon
- Molecular Biology top 10%
- Cellular and Molecular Neuroscience top 2%
- Physiology top 5%
- Neurology top 1%
- Neurology top 2%
- Co-authors
- Yael Stern-BachGeoffrey A. KerchnerMorgan ShengIngileif B. HallgrímsdóttirAndrew SingletonRobert GrahamDavid A. HindsTushar Bhangale
- Topics
- Alzheimer's disease research and treatments (5 papers)Neuroscience and Neuropharmacology Research (5 papers)Muscle Physiology and Disorders (3 papers)
- Partner nations
- United StatesFranceIsrael
In The Last Decade
Gai Ayalon
17 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Molecular Biology 991
- Cellular and Molecular Neuroscience 799
- Physiology 619
- Neurology 586
- Neurology 548
Countries citing papers authored by Gai Ayalon
This map shows the geographic impact of Gai Ayalon'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 Gai Ayalon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gai Ayalon more than expected).
Fields of papers citing papers by Gai Ayalon
This network shows the impact of papers produced by Gai Ayalon. 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 Gai Ayalon. The network helps show where Gai Ayalon may publish in the future.
Co-authorship network of co-authors of Gai Ayalon
This figure shows the co-authorship network connecting the top 25 collaborators of Gai Ayalon. A scholar is included among the top collaborators of Gai Ayalon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gai Ayalon. Gai Ayalon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 7 | |
| 3 | 14 | |
| 4 | 82 | |
| 5 | 37 | |
| 6 | 17 | |
| 7 | Diverse Brain Myeloid Expression Profiles Reveal Distinct Microglial Activation States and Aspects of Alzheimer’s Disease Not Evident in Mouse Modelsbreakdown → | 445 |
| 8 | A meta-analysis of genome-wide association studies identifies 17 new Parkinson's disease risk locibreakdown → | 772 |
| 9 | 10 | |
| 10 | 1 | |
| 11 | 14 | |
| 12 | 69 | |
| 13 | 42 | |
| 14 | 110 | |
| 15 | 206 | |
| 16 | 54 | |
| 17 | 200 |
About Gai Ayalon
Gai Ayalon is a scholar working on Cellular and Molecular Neuroscience, Physiology and Developmental Neuroscience, having authored 17 papers that have together received 2.1k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (5 papers), Neuroscience and Neuropharmacology Research (5 papers) and Muscle Physiology and Disorders (3 papers). The work is most often cited by research in Neurology (586 citations), Cellular and Molecular Neuroscience (799 citations) and Neurology (548 citations). Gai Ayalon has collaborated with scholars based in United States, France and Israel. Frequent co-authors include Yael Stern-Bach, Geoffrey A. Kerchner, Morgan Sheng, Ingileif B. Hallgrímsdóttir, Andrew Singleton, Robert Graham, David A. Hinds, Tushar Bhangale, Marcel van der Brug and Baris Bingol. Their work appears in journals such as Cell, Journal of Biological Chemistry and Neuron.
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.