Or Zuk
- Cancer Research top 0.1%
- Molecular Biology top 0.5%
- RNA and protein synthesis mechanisms 5
- Gene expression and cancer classification 5
- Bioinformatics and Genomic Networks 5
- Genomics and Chromatin Dynamics 4
- RNA Research and Splicing 4
- Single-cell and spatial transcriptomics 3
- Genomics and Phylogenetic Studies 3
- Genetics top 1%
- Endocrinology top 2%
- Immunology top 5%
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- Bayesian Methods and Mixture Models 7
Or Zuk
36 papers receiving 8.8k citations
Hit Papers
Peers
Comparison fields: 5 of 182
- Cancer Research 4.7k
- Molecular Biology 6.4k
- Genetics 1.7k
- Endocrinology 230
- Immunology 595
Countries citing papers authored by Or Zuk
This map shows the geographic impact of Or Zuk'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 Or Zuk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Or Zuk more than expected).
Fields of papers citing papers by Or Zuk
This network shows the impact of papers produced by Or Zuk. 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 Or Zuk. The network helps show where Or Zuk may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Or Zuk, 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 | 2025 | 0 | |
| 2 | 2023 | 0 | |
| 3 | 2021 | 40 | |
| 4 | 2021 | 17 | |
| 5 | 2020 | 14 | |
| 6 | 2019 | 158 | |
| 7 | 2013 | 253 | |
| 8 | 2013 | 143 | |
| 9 | The mystery of missing heritability: Genetic interactions create phantom heritabilitybreakdown → | 2012 | 1007 |
| 10 | Ranking Under Uncertainty. | 2012 | 1 |
| 11 | 2011 | 21 | |
| 12 | 2011 | 16 | |
| 13 | 2010 | 34 | |
| 14 | A Large Intergenic Noncoding RNA Induced by p53 Mediates Global Gene Repression in the p53 Responsebreakdown → | 2010 | 1688 |
| 15 | 2009 | 89 | |
| 16 | 2007 | 49 | |
| 17 | On the number of samples needed to learn the correct structure of a Bayesian network | 2006 | 13 |
| 18 | The Relative Entropy Rate For Two Hidden Markov Processes | 2006 | 2 |
| 19 | 2005 | 113 | |
| 20 | 2005 | 29 |
About Or Zuk
Or Zuk is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology, having authored 38 papers that have together received 8.9k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (7 papers), RNA and protein synthesis mechanisms (5 papers), Gene expression and cancer classification (5 papers), Bioinformatics and Genomic Networks (5 papers), Genomics and Chromatin Dynamics (4 papers), RNA Research and Splicing (4 papers), Single-cell and spatial transcriptomics (3 papers) and Genomics and Phylogenetic Studies (3 papers). The work is most often cited by research in Cancer Research (4.7k citations), Molecular Biology (6.4k citations) and Genetics (1.7k citations). Or Zuk has collaborated with scholars based in Israel, United States and Italy. Frequent co-authors include Eric S. Lander, Aviv Regev, Manuel Garber, Eliana Hechter, Shamil Sunyaev, Ido Amit, David M. Feldser, Mitchell Guttman, Tyler Jacks and Maite Huarte. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications, Nature, Cell and SIAM Journal on Financial Mathematics.
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.