Orit Lavi
Impact in
- Modeling and Simulation top 2%
- Mathematical Biology Tumor Growth
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- Cancer Genomics and Diagnostics
Papers in
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- Mathematical Biology Tumor Growth 8
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- Gene Regulatory Network Analysis 3
- Single-cell and spatial transcriptomics 2
- Co-authors
- Michael M. Gottesman (8 shared papers)Jean-Pierre Gillet (1 shared paper)Matthew D. Hall (1 shared paper)Doron Levy (6 shared papers)James M. Greene (5 shared papers)Mark R. Gilbert (1 shared paper)Orieta Celiku (1 shared paper)Yoram Louzoun (3 shared papers)
- Journals
- Cancer Research (3 papers)Bulletin of Mathematical Biology (2 papers)Nature Communications (1 paper)BMC Systems Biology (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)
- Partner nations
- United StatesIsraelBelgium
In The Last Decade
Orit Lavi
15 papers receiving 599 citations
Peers
Comparison fields: 5 of 81
- Modeling and Simulation 138
- Cancer Research 137
- Oncology 193
- Molecular Biology 300
- Cell Biology 61
Countries citing papers authored by Orit Lavi
This map shows the geographic impact of Orit Lavi'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 Orit Lavi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Orit Lavi more than expected).
Fields of papers citing papers by Orit Lavi
This network shows the impact of papers produced by Orit Lavi. 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 Orit Lavi. The network helps show where Orit Lavi may publish in the future.
Co-authors
The 18 scholars most cited alongside Orit Lavi, 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 | 2015 | 269 | |
| 2 | 2012 | 74 | |
| 3 | 2015 | 56 | |
| 4 | 2013 | 49 | |
| 5 | 2014 | 31 | |
| 6 | 2014 | 26 | |
| 7 | 2016 | 20 | |
| 8 | 2014 | 18 | |
| 9 | 2019 | 17 | |
| 10 | 2008 | 11 | |
| 11 | 2020 | 10 | |
| 12 | 2014 | 8 | |
| 13 | 2011 | 7 | |
| 14 | 2020 | 7 | |
| 15 | 2010 | 1 |
About Orit Lavi
Orit Lavi is a scholar working on Modeling and Simulation, Molecular Biology, Oncology, Cancer Research and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 604 indexed citations. Recurring topics across this work include Mathematical Biology Tumor Growth (8 papers), Cancer Genomics and Diagnostics (4 papers), Drug Transport and Resistance Mechanisms (3 papers), Gene Regulatory Network Analysis (3 papers), Microtubule and mitosis dynamics (2 papers), Listeria monocytogenes in Food Safety (2 papers), Single-cell and spatial transcriptomics (2 papers) and Cell Image Analysis Techniques (2 papers). The work is most often cited by research in Modeling and Simulation (138 citations), Cancer Research (137 citations), Oncology (193 citations), Molecular Biology (300 citations) and Cell Biology (61 citations). Orit Lavi has collaborated with scholars based in United States, Israel and Belgium. Frequent co-authors include Michael M. Gottesman, Jean-Pierre Gillet, Matthew D. Hall, Doron Levy, James M. Greene, Mark R. Gilbert, Orieta Celiku, Yoram Louzoun, Eyal Klement and Paloma Silva de Souza. Their work appears in journals such as Cancer Research, Bulletin of Mathematical Biology, Nature Communications, BMC Systems Biology and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.