Modeling cancer in mice
Oncogene, ISSN: 0950-9232, Vol: 21, Issue: 35 REV. ISS. 3, Page: 5504-5514
2002
- 28Citations
- 45Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations28
- Citation Indexes28
- 28
- CrossRef26
- Captures45
- Readers45
- 45
Review Description
The laboratory mouse is one of the most powerful tools for both gene discovery and validation in cancer genetics. Recent technological advances in engineering the mouse genome with chromosome translocations, latent alleles, and tissue-specific and temporally regulated mutations have provided more exacting models of human disease. The marriage of mouse tumor models with rapidly evolving methods to profile genetic and epigenetic alterations in tumors, and to finely map genetic modifier loci, will continue to provide insight into the key pathways leading to tumorigenesis. These discoveries hold great promise for identifying relevant drug targets for treating human cancer.
Bibliographic Details
Springer Science and Business Media LLC
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