Noa Novershtern
Impact in
- Molecular Biology top 10%
- Pluripotent Stem Cells Research
- CRISPR and Genetic Engineering
- Epigenetics and DNA Methylation
- Renal and related cancers
- Genomics and Chromatin Dynamics
- RNA modifications and cancer
- Aging top 10%
Papers in
-
- Pluripotent Stem Cells Research 4
- CRISPR and Genetic Engineering 4
- Epigenetics and DNA Methylation 2
- Gene expression and cancer classification 1
- Co-authors
- Jacob H. Hanna (6 shared papers)Leehee Weinberger (3 shared papers)Muneef Ayyash (2 shared papers)Sergey Viukov (3 shared papers)Nir Friedman (3 shared papers)Asaf Zviran (2 shared papers)Vladislav Krupalnik (2 shared papers)Shay Geula (2 shared papers)
- Journals
- Bioinformatics (1 paper)Human Molecular Genetics (1 paper)IEEE Transactions on Artificial Intelligence (1 paper)Nature Biotechnology (1 paper)Nature (1 paper)
- Partner nations
- IsraelUnited StatesUnited Arab Emirates
In The Last Decade
Noa Novershtern
9 papers receiving 992 citations
Noa Novershtern's Hit Papers
Peers
Comparison fields: 5 of 75
- Molecular Biology 906
- Aging 22
- Developmental Neuroscience 20
- Genetics 108
- Genetics 27
Countries citing papers authored by Noa Novershtern
This map shows the geographic impact of Noa Novershtern'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 Noa Novershtern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noa Novershtern more than expected).
Fields of papers citing papers by Noa Novershtern
This network shows the impact of papers produced by Noa Novershtern. 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 Noa Novershtern. The network helps show where Noa Novershtern may publish in the future.
Co-authors
The 25 scholars most cited alongside Noa Novershtern, 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 | Dynamic stem cell states: naive to primed pluripotency in rodents and humans Hit paper breakdown → | 2016 | 449 |
| 2 | 2012 | 277 | |
| 3 | 2015 | 103 | |
| 4 | 2007 | 43 | |
| 5 | 2008 | 42 | |
| 6 | 2022 | 36 | |
| 7 | 2011 | 33 | |
| 8 | 2020 | 22 | |
| 9 | 2023 | 2 | |
| 10 | 2024 | 0 | |
| 11 | 2025 | 0 |
About Noa Novershtern
Noa Novershtern is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition, Epidemiology and Artificial Intelligence, having authored 11 papers that have together received 1.0k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (4 papers), CRISPR and Genetic Engineering (4 papers), Epigenetics and DNA Methylation (2 papers), COVID-19 diagnosis using AI (1 paper), Gene expression and cancer classification (1 paper), Medical Image Segmentation Techniques (1 paper), Brain Tumor Detection and Classification (1 paper) and Animal Genetics and Reproduction (1 paper). The work is most often cited by research in Molecular Biology (906 citations), Aging (22 citations), Developmental Neuroscience (20 citations), Genetics (108 citations) and Genetics (27 citations). Noa Novershtern has collaborated with scholars based in Israel, United States and United Arab Emirates. Frequent co-authors include Jacob H. Hanna, Leehee Weinberger, Muneef Ayyash, Sergey Viukov, Nir Friedman, Asaf Zviran, Vladislav Krupalnik, Shay Geula, Mirie Zerbib and Itay Maza. Their work appears in journals such as Bioinformatics, Human Molecular Genetics, IEEE Transactions on Artificial Intelligence, Nature Biotechnology 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.