Aya Narunsky
Impact in
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- Electron Spin Resonance Studies
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- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
Papers in
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- Protein Structure and Dynamics 6
- RNA and protein synthesis mechanisms 4
- Genomics and Phylogenetic Studies 3
- Bioinformatics and Genomic Networks 2
- Machine Learning in Bioinformatics 2
- RNA modifications and cancer 2
- RNA Research and Splicing 2
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- Enzyme Structure and Function 2
- Co-authors
- Nir Ben‐Tal (7 shared papers)Amit Kessel (2 shared papers)Haim Ashkenazy (3 shared papers)Gal Masrati (1 shared paper)Rachel Kolodny (4 shared papers)Sharon Ruthstein (1 shared paper)Tamar Juven‐Gershon (1 shared paper)Vikram Alva (1 shared paper)
- Journals
- Structure (2 papers)BMC Bioinformatics (2 papers)Nature Communications (1 paper)Microbial Genomics (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Aya Narunsky
10 papers receiving 252 citations
Peers
Comparison fields: 5 of 70
- Biophysics 17
- Molecular Biology 178
- Nutrition and Dietetics 21
- Endocrinology 6
- Computational Theory and Mathematics 16
Countries citing papers authored by Aya Narunsky
This map shows the geographic impact of Aya Narunsky'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 Aya Narunsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aya Narunsky more than expected).
Fields of papers citing papers by Aya Narunsky
This network shows the impact of papers produced by Aya Narunsky. 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 Aya Narunsky. The network helps show where Aya Narunsky may publish in the future.
Co-authors
The 14 scholars most cited alongside Aya Narunsky, 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 | 2019 | 147 | |
| 2 | 2017 | 44 | |
| 3 | 2020 | 27 | |
| 4 | 2015 | 12 | |
| 5 | 2024 | 9 | |
| 6 | 2018 | 3 | |
| 7 | 2023 | 3 | |
| 8 | 2015 | 3 | |
| 9 | 2025 | 2 | |
| 10 | 2014 | 2 |
About Aya Narunsky
Aya Narunsky is a scholar working on Molecular Biology, Materials Chemistry, Astronomy and Astrophysics, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 10 papers that have together received 252 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (4 papers), Genomics and Phylogenetic Studies (3 papers), Enzyme Structure and Function (2 papers), Bioinformatics and Genomic Networks (2 papers), Machine Learning in Bioinformatics (2 papers), RNA modifications and cancer (2 papers) and RNA Research and Splicing (2 papers). The work is most often cited by research in Biophysics (17 citations), Molecular Biology (178 citations), Nutrition and Dietetics (21 citations), Endocrinology (6 citations) and Computational Theory and Mathematics (16 citations). Aya Narunsky has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Nir Ben‐Tal, Amit Kessel, Haim Ashkenazy, Gal Masrati, Rachel Kolodny, Sharon Ruthstein, Tamar Juven‐Gershon, Vikram Alva, Ronald R. Breaker and Kumari Kavita. Their work appears in journals such as Structure, BMC Bioinformatics, Nature Communications, Microbial Genomics and Nucleic Acids Research.
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.