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
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- Single-cell and spatial transcriptomics 2
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- Sarcoma Diagnosis and Treatment 4
- Veterinary Oncology Research 3
- Co-authors
- Craig P. Webb (12 shared papers)William F. Punch (3 shared papers)Pavol Juhás (2 shared papers)Simon J. L. Billinge (2 shared papers)Phillip M. Duxbury (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)Pediatric Blood & Cancer (1 paper)Clinical Cancer Research (1 paper)Neoplasia (1 paper)
- Partner nations
- United StatesSouth KoreaAustralia
In The Last Decade
David Cherba
23 papers receiving 957 citations
Peers
Comparison fields: 5 of 117
- Cancer Research 334
- Genetics 102
- Oncology 233
- Molecular Biology 489
- Biotechnology 51
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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 176 | |
| 2 | 2006 | 148 | |
| 3 | 2014 | 123 | |
| 4 | 2010 | 105 | |
| 5 | 2009 | 91 | |
| 6 | 2012 | 55 | |
| 7 | 2013 | 47 | |
| 8 | 2015 | 45 | |
| 9 | 2014 | 26 | |
| 10 | 2011 | 21 | |
| 11 | Melanoma patient derived xenografts acquire distinct Vemurafenib resistance mechanisms. | 2015 | 21 |
| 12 | 2015 | 21 | |
| 13 | 2015 | 20 | |
| 14 | 2014 | 16 | |
| 15 | 2013 | 14 | |
| 16 | 2013 | 13 | |
| 17 | 2012 | 12 | |
| 18 | 2006 | 7 | |
| 19 | 2014 | 6 | |
| 20 | 2004 | 5 |
About David Cherba
David Cherba is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Oncology, Cancer Research and Genetics, having authored 25 papers that have together received 978 indexed citations. Recurring topics across this work include Sarcoma Diagnosis and Treatment (4 papers), MicroRNA in disease regulation (3 papers), Computational Drug Discovery Methods (3 papers), Cancer Cells and Metastasis (3 papers), Virus-based gene therapy research (3 papers), Veterinary Oncology Research (3 papers), Cancer Genomics and Diagnostics (3 papers) and Single-cell and spatial transcriptomics (2 papers). The work is most often cited by research in Cancer Research (334 citations), Genetics (102 citations), Oncology (233 citations), Molecular Biology (489 citations) and Biotechnology (51 citations). David Cherba has collaborated with scholars based in United States, South Korea and Australia. Frequent co-authors include Craig P. Webb, William F. Punch, Pavol Juhás, Simon J. L. Billinge, Phillip M. Duxbury, 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, Pediatric Blood & Cancer, Clinical Cancer Research and Neoplasia.
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.