Association of single nucleotide polymorphisms in selenoprotein genes with cancer risk
Methods in Molecular Biology, ISSN: 1064-3745, Vol: 1661, Page: 313-324
2018
- 10Citations
- 14Captures
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
- Citations10
- Citation Indexes10
- 10
- CrossRef4
- Captures14
- Readers14
- 14
Book Chapter Description
Genetic association studies have linked genetic variants in the Selenium (Se) metabolism with the development of complex diseases such as cancer and helped unravel novel mechanisms underlying cancer development. The chapter describes the specificity of genetic variants in the Se metabolism, the approaches used in association studies, and the limitations of such approaches.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85029591585&origin=inward; http://dx.doi.org/10.1007/978-1-4939-7258-6_22; http://www.ncbi.nlm.nih.gov/pubmed/28917054; http://link.springer.com/10.1007/978-1-4939-7258-6_22; https://dx.doi.org/10.1007/978-1-4939-7258-6_22; https://link.springer.com/protocol/10.1007/978-1-4939-7258-6_22
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know