David Cherba
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer Genomics and Diagnostics
- Genetics top 5%
- Glioma Diagnosis and Treatment
- Genomic variations and chromosomal abnormalities
Papers in
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- Cancer Genomics and Diagnostics 2
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- Veterinary Oncology Research 3
- Sarcoma Diagnosis and Treatment 2
- Co-authors
- Craig Paul Webb (13 shared papers)William F. Punch (2 shared papers)Simon J. L. Billinge (1 shared paper)Pavol Juhás (1 shared paper)Phillip M. Duxbury (1 shared paper)Ana C. deCarvalho (2 shared papers)Laila Poisson (2 shared papers)Tom Mikkelsen (2 shared papers)
- Journals
- Journal of Translational Medicine (4 papers)PLoS ONE (3 papers)Tire Science and Technology (1 paper)Pediatric Blood & Cancer (1 paper)Nature (1 paper)
- Partner nations
- United StatesSouth KoreaRussia
In The Last Decade
David Cherba
23 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 101
- Cancer Research 243
- Genetics 157
- Oncology 137
- Molecular Biology 259
- Genetics 114
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 | 230 | |
| 2 | 2006 | 166 | |
| 3 | 2014 | 137 | |
| 4 | 2010 | 113 | |
| 5 | 2009 | 99 | |
| 6 | 2012 | 58 | |
| 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 | 9 | |
| 19 | 2014 | 6 | |
| 20 | 2004 | 5 |
About David Cherba
David Cherba is a scholar working on Cancer Research, Pulmonary and Respiratory Medicine, Genetics, Oncology and Neurology, having authored 24 papers that have together received 1.1k indexed citations. Recurring topics across this work include Veterinary Oncology Research (3 papers), Glioma Diagnosis and Treatment (2 papers), Sarcoma Diagnosis and Treatment (2 papers), Bioinformatics and Genomic Networks (2 papers), Cancer Genomics and Diagnostics (2 papers), Melanoma and MAPK Pathways (2 papers), X-ray Diffraction in Crystallography (1 paper) and Reinforcement Learning in Robotics (1 paper). The work is most often cited by research in Cancer Research (243 citations), Genetics (157 citations), Oncology (137 citations), Molecular Biology (259 citations) and Genetics (114 citations). David Cherba has collaborated with scholars based in United States, South Korea and Russia. Frequent co-authors include Craig Paul Webb, William F. Punch, Simon J. L. Billinge, Pavol Juhás, Phillip M. Duxbury, Ana C. deCarvalho, Laila Poisson, Tom Mikkelsen, Mary E. Winn and Yuri Nikolsky. Their work appears in journals such as Journal of Translational Medicine, PLoS ONE, Tire Science and Technology, Pediatric Blood & Cancer and Nature.
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.