David Cherba
Impact in
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Genetics top 10%
- Glioma Diagnosis and Treatment
Papers in
-
- Cancer Genomics and Diagnostics 2
- MicroRNA in disease regulation 1
- Oncology 4
- Cancer Cells and Metastasis 2
- Co-authors
- Craig Paul Webb (13 shared papers)William F. Punch (2 shared papers)Phillip M. Duxbury (1 shared paper)Simon J. L. Billinge (1 shared paper)Pavol Juhás (1 shared paper)Laila Poisson (2 shared papers)Ana C. deCarvalho (2 shared papers)Tom Mikkelsen (2 shared papers)
- Journals
- Journal of Translational Medicine (4 papers)PLoS ONE (3 papers)Neoplasia (1 paper)Journal of Thoracic Oncology (1 paper)Nature Genetics (1 paper)
- Partner nations
- United StatesAustraliaSouth Korea
In The Last Decade
David Cherba
23 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 114
- Cancer Research 338
- Genetics 112
- Oncology 222
- Molecular Biology 496
- Biotechnology 52
Countries citing papers authored by David Cherba
This map shows the geographic impact of David Cherba'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 David Cherba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Cherba more than expected).
Fields of papers citing papers by David Cherba
This network shows the impact of papers produced by David Cherba. 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 David Cherba. The network helps show where David Cherba may publish in the future.
Co-authors
The 25 scholars most cited alongside David Cherba, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 222 | |
| 2 | 2006 | 162 | |
| 3 | 2014 | 137 | |
| 4 | 2010 | 113 | |
| 5 | 2009 | 99 | |
| 6 | 2012 | 57 | |
| 7 | 2013 | 52 | |
| 8 | 2015 | 46 | |
| 9 | 2014 | 29 | |
| 10 | Melanoma patient derived xenografts acquire distinct Vemurafenib resistance mechanisms. | 2015 | 27 |
| 11 | 2015 | 24 | |
| 12 | 2015 | 22 | |
| 13 | 2011 | 21 | |
| 14 | 2014 | 19 | |
| 15 | 2012 | 15 | |
| 16 | 2013 | 15 | |
| 17 | 2013 | 13 | |
| 18 | 2006 | 8 | |
| 19 | 2014 | 6 | |
| 20 | 2004 | 5 |
About David Cherba
David Cherba is a scholar working on Cancer Research, Oncology, Molecular Biology, Computational Theory and Mathematics and Media Technology, having authored 24 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), Veterinary Oncology Research (3 papers), Cancer Genomics and Diagnostics (2 papers), Single-cell and spatial transcriptomics (2 papers), Cancer Cells and Metastasis (2 papers), Bioinformatics and Genomic Networks (2 papers), Melanoma and MAPK Pathways (2 papers) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Cancer Research (338 citations), Genetics (112 citations), Oncology (222 citations), Molecular Biology (496 citations) and Biotechnology (52 citations). David Cherba has collaborated with scholars based in United States, Australia and South Korea. Frequent co-authors include Craig Paul Webb, William F. Punch, Phillip M. Duxbury, Simon J. L. Billinge, Pavol Juhás, Laila Poisson, Ana C. deCarvalho, Tom Mikkelsen, Mary E. Winn and Yuri Nikolsky. Their work appears in journals such as Journal of Translational Medicine, PLoS ONE, Neoplasia, Journal of Thoracic Oncology and Nature Genetics.
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.