Gad Getz
Impact in
- Cancer Research top 0.01%
- Cancer Genomics and Diagnostics
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 0.05%
- RNA modifications and cancer
- Epigenetics and DNA Methylation
- Circular RNAs in diseases
Papers in
-
- Bioinformatics and Genomic Networks 17
- Epigenetics and DNA Methylation 16
- Gene expression and cancer classification 16
- Genomics and Phylogenetic Studies 14
- Cancer Research 100
- Cancer Genomics and Diagnostics 90
- Co-authors
- Todd R. Golub (11 shared papers)Matthew Meyerson (24 shared papers)Scott L. Carter (19 shared papers)Michael S. Lawrence (35 shared papers)Rameen Beroukhim (21 shared papers)Craig H. Mermel (6 shared papers)Stacey Gabriel (18 shared papers)Benjamin L. Ebert (7 shared papers)
- Journals
- Blood (39 papers)Cancer Research (31 papers)Journal of Clinical Oncology (15 papers)Bioinformatics (11 papers)Nature Genetics (9 papers)
- Partner nations
- United StatesIsraelGermany
In The Last Decade
Gad Getz
217 papers receiving 42.8k citations
Gad Getz's Hit Papers
Peers
Comparison fields: 5 of 179
- Cancer Research 15.7k
- Molecular Biology 23.8k
- Oncology 8.6k
- Pulmonary and Respiratory Medicine 6.1k
- Pathology and Forensic Medicine 3.3k
Countries citing papers authored by Gad Getz
This map shows the geographic impact of Gad Getz'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 Gad Getz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gad Getz more than expected).
Fields of papers citing papers by Gad Getz
This network shows the impact of papers produced by Gad Getz. 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 Gad Getz. The network helps show where Gad Getz may publish in the future.
Co-authors
The 25 scholars most cited alongside Gad Getz, 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 227 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | MicroRNA expression profiles classify human cancers Hit paper breakdown → | 2005 | 7841 |
| 2 | Inferring tumour purity and stromal and immune cell admixture from expression data Hit paper breakdown → | 2013 | 6306 |
| 3 | Molecular and Genetic Properties of Tumors Associated with Local Immune Cytolytic Activity Hit paper breakdown → | 2015 | 2559 |
| 4 | Discovery and saturation analysis of cancer genes across 21 tumour types Hit paper breakdown → | 2014 | 2086 |
| 5 | GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers Hit paper breakdown → | 2011 | 2051 |
| 6 | Pan-cancer patterns of somatic copy number alteration Hit paper breakdown → | 2013 | 1260 |
| 7 | Absolute quantification of somatic DNA alterations in human cancer Hit paper breakdown → | 2012 | 1163 |
| 8 | Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma Hit paper breakdown → | 2005 | 1114 |
| 9 | BRAF mutation predicts sensitivity to MEK inhibition Hit paper breakdown → | 2005 | 1015 |
| 10 | An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers Hit paper breakdown → | 2013 | 844 |
| 11 | Advances in understanding cancer genomes through second-generation sequencing Hit paper breakdown → | 2010 | 798 |
| 12 | Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes Hit paper breakdown → | 2014 | 596 |
| 13 | Outcome signature genes in breast cancer: is there a unique set? Hit paper breakdown → | 2004 | 581 |
| 14 | Coupled two-way clustering analysis of gene microarray data Hit paper breakdown → | 2000 | 545 |
| 15 | RNA-SeQC: RNA-seq metrics for quality control and process optimization Hit paper breakdown → | 2012 | 511 |
| 16 | Genomic sequencing of meningiomas identifies oncogenic SMO and AKT1 mutations Hit paper breakdown → | 2013 | 429 |
| 17 | 2015 | 412 | |
| 18 | TET2 mutations predict response to hypomethylating agents in myelodysplastic syndrome patients Hit paper breakdown → | 2014 | 408 |
| 19 | 2008 | 370 | |
| 20 | 2013 | 366 |
About Gad Getz
Gad Getz is a scholar working on Molecular Biology, Cancer Research, Oncology, Pathology and Forensic Medicine and Genetics, having authored 227 papers that have together received 43.3k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (90 papers), Chronic Lymphocytic Leukemia Research (26 papers), Genetic factors in colorectal cancer (23 papers), Bioinformatics and Genomic Networks (17 papers), Epigenetics and DNA Methylation (16 papers), Gene expression and cancer classification (16 papers), Multiple Myeloma Research and Treatments (15 papers) and Genomics and Phylogenetic Studies (14 papers). The work is most often cited by research in Cancer Research (15.7k citations), Molecular Biology (23.8k citations), Oncology (8.6k citations), Pulmonary and Respiratory Medicine (6.1k citations) and Pathology and Forensic Medicine (3.3k citations). Gad Getz has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Todd R. Golub, Matthew Meyerson, Scott L. Carter, Michael S. Lawrence, Rameen Beroukhim, Craig H. Mermel, Stacey Gabriel, Benjamin L. Ebert, Catherine J. Wu and Peter W. Laird. Their work appears in journals such as Blood, Cancer Research, Journal of Clinical Oncology, Bioinformatics 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.