Rebecca Kusko
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- Genetic Neurodegenerative Diseases 3
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- Computational Drug Discovery Methods 5
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- RNA modifications and cancer 4
- Gene expression and cancer classification 3
- Molecular Biology Techniques and Applications 3
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- Cancer Genomics and Diagnostics 5
- Cancer-related molecular mechanisms research 3
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- SARS-CoV-2 and COVID-19 Research 2
- Co-authors
- Yoonjeong ChaIris GrossmanMichael R. HaydenMichal GevaBenjamin ZeskindSpyros PapapetropoulosJeffrey RossIan J. Reynolds
- Cited by
- Biological PsychiatryCellular and Molecular NeuroscienceComputational Theory and Mathematics
- Journals
- SHILAP Revista de lepidopterología (1 paper)Nature Biotechnology (1 paper)Neurology (1 paper)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Rebecca Kusko
29 papers receiving 876 citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Biological Psychiatry 28
- Cellular and Molecular Neuroscience 182
- Computational Theory and Mathematics 152
- Health Informatics 10
- Molecular Biology 457
Countries citing papers authored by Rebecca Kusko
This map shows the geographic impact of Rebecca Kusko'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 Rebecca Kusko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rebecca Kusko more than expected).
Fields of papers citing papers by Rebecca Kusko
This network shows the impact of papers produced by Rebecca Kusko. 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 Rebecca Kusko. The network helps show where Rebecca Kusko may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rebecca Kusko, 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 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2022 | 2 | |
| 4 | 2021 | 11 | |
| 5 | 2021 | 6 | |
| 6 | 2020 | 11 | |
| 7 | 2020 | 63 | |
| 8 | 2020 | 70 | |
| 9 | 2019 | 42 | |
| 10 | 2018 | 35 | |
| 11 | 2018 | 33 | |
| 12 | 2018 | 4 | |
| 13 | 2017 | 19 | |
| 14 | Drug repurposing from the perspective of pharmaceutical companiesbreakdown → | 2017 | 269 |
| 15 | 2017 | 18 | |
| 16 | 2016 | 105 | |
| 17 | 2014 | 36 | |
| 18 | Comparison of Illumina and Ion Torrent RNA-Sequencing and Microarray-based approaches for Profiling the Transcriptome. | 2014 | 2 |
| 19 | 2013 | 1 | |
| 20 | 2012 | 24 |
About Rebecca Kusko
Rebecca Kusko is a scholar working on Cancer Research, Biophysics and Computational Theory and Mathematics, having authored 30 papers that have together received 887 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (5 papers), Computational Drug Discovery Methods (5 papers), RNA modifications and cancer (4 papers), Genetic Neurodegenerative Diseases (3 papers), Cancer-related molecular mechanisms research (3 papers), Gene expression and cancer classification (3 papers), Molecular Biology Techniques and Applications (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Biological Psychiatry (28 citations), Cellular and Molecular Neuroscience (182 citations) and Computational Theory and Mathematics (152 citations). Rebecca Kusko has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Yoonjeong Cha, Iris Grossman, Michael R. Hayden, Michal Geva, Benjamin Zeskind, Spyros Papapetropoulos, Jeffrey Ross, Ian J. Reynolds, Deepak Kumar and Gregory Koytiger. Their work appears in journals such as SHILAP Revista de lepidopterología, Nature Biotechnology and Neurology.
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.