Shalev Itzkovitz
- Neurology top 0.1%
- Statistical and Nonlinear Physics top 0.1%
- Complex Network Analysis Techniques 8
- Biological Psychiatry top 0.5%
- Molecular Biology top 0.2%
- Single-cell and spatial transcriptomics 27
- Gene Regulatory Network Analysis 20
- RNA Research and Splicing 9
- RNA and protein synthesis mechanisms 8
- Aging top 1%
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- Cancer Cells and Metastasis 14
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- Cancer Genomics and Diagnostics 14
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- Pancreatic function and diabetes 9
- Co-authors
- Uri AlonRon MiloNadav KashtanShai S. Shen-OrrDmitri B. ChklovskiiBeáta TóthIdo AmitEyal David
- Partner nations
- IsraelUnited StatesSwitzerland
In The Last Decade
Shalev Itzkovitz
104 papers receiving 20.0k citations
Hit Papers
Peers
Comparison fields: 5 of 213
- Neurology 2.7k
- Statistical and Nonlinear Physics 2.5k
- Biological Psychiatry 450
- Molecular Biology 11.1k
- Aging 259
Countries citing papers authored by Shalev Itzkovitz
This map shows the geographic impact of Shalev Itzkovitz'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 Shalev Itzkovitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shalev Itzkovitz more than expected).
Fields of papers citing papers by Shalev Itzkovitz
This network shows the impact of papers produced by Shalev Itzkovitz. 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 Shalev Itzkovitz. The network helps show where Shalev Itzkovitz may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shalev Itzkovitz, 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 | 2024 | 1 | |
| 2 | 2023 | 6 | |
| 3 | 2022 | 31 | |
| 4 | 2022 | 5 | |
| 5 | 2021 | 43 | |
| 6 | 2021 | 33 | |
| 7 | 2020 | 100 | |
| 8 | 2018 | 17 | |
| 9 | 2018 | 213 | |
| 10 | 2017 | 117 | |
| 11 | 2017 | 13 | |
| 12 | Pax6 role in the regulation of retinal pigmented epithelium maturation | 2016 | 1 |
| 13 | 2014 | 129 | |
| 14 | 2013 | 143 | |
| 15 | Slug and Sox9 Cooperatively Determine the Mammary Stem Cell Statebreakdown → | 2012 | 755 |
| 16 | 2008 | 54 | |
| 17 | 2008 | 41 | |
| 18 | Uniform generation of random graphs with arbitrary degree sequences | 2003 | 24 |
| 19 | Network motifs in biological networks: Roles and Generalizations | 2003 | 1 |
| 20 | Network Motifs: Simple Building Blocks of Complex Networksbreakdown → | 2002 | 4738 |
About Shalev Itzkovitz
Shalev Itzkovitz is a scholar working on Aging, Cancer Research and Molecular Biology, having authored 106 papers that have together received 20.4k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (27 papers), Gene Regulatory Network Analysis (20 papers), Cancer Cells and Metastasis (14 papers), Cancer Genomics and Diagnostics (14 papers), Pancreatic function and diabetes (9 papers), RNA Research and Splicing (9 papers), RNA and protein synthesis mechanisms (8 papers) and Complex Network Analysis Techniques (8 papers). The work is most often cited by research in Neurology (2.7k citations), Statistical and Nonlinear Physics (2.5k citations) and Biological Psychiatry (450 citations). Shalev Itzkovitz has collaborated with scholars based in Israel, United States and Switzerland. Frequent co-authors include Uri Alon, Ron Milo, Nadav Kashtan, Shai S. Shen-Orr, Dmitri B. Chklovskii, Beáta Tóth, Ido Amit, Eyal David, Orit Matcovitch-Natan and Keren Bahar Halpern. Their work appears in journals such as Cell, Nature, PLoS Computational Biology, Science and Molecular Systems Biology.
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.