Characterization and prediction of mRNA polyadenylation sites in human genes
Medical and Biological Engineering and Computing, ISSN: 0140-0118, Vol: 49, Issue: 4, Page: 463-472
2011
- 17Citations
- 19Captures
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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.
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Metrics Details
- Citations17
- Citation Indexes17
- 17
- CrossRef12
- Captures19
- Readers19
- 19
Article Description
The accurate identification of potential poly(A) sites has contributed to all many studies with regard to alternative polyadenylation. The aim of this study was the development of a machine-learning methodology that will help to discriminate real polyadenylation signals from randomly occurring signals in genomic sequence. Since previous studies have revealed that RNA secondary structure in certain genes has significant impact, the authors tried to computationally pinpoint common structural patterns around the poly(A) sites and to investigate how RNA secondary structure may influence polyadenylation. This involved an initial study on the impact of RNA structure and it was found using motif search tools that hairpin structures might be important. Thus, it was propose that, in addition to the sequence pattern around poly(A) sites, there exists a widespread structural pattern that is also employed during human mRNA polyadenylation. In this study, the authors present a computational model that uses support vector machines to predict human poly(A) sites. The results show that this predictive model has a comparable performance to the current prediction tool. In addition, it was identified common structural patterns associated with polyadenylation using several motif finding programs and this provides new insight into the role of RNA secondary structure plays in polyadenylation. © 2011 International Federation for Medical and Biological Engineering.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=79955622645&origin=inward; http://dx.doi.org/10.1007/s11517-011-0732-4; http://www.ncbi.nlm.nih.gov/pubmed/21286831; http://link.springer.com/10.1007/s11517-011-0732-4; https://dx.doi.org/10.1007/s11517-011-0732-4; https://link.springer.com/article/10.1007/s11517-011-0732-4; http://www.springerlink.com/index/10.1007/s11517-011-0732-4; http://www.springerlink.com/index/pdf/10.1007/s11517-011-0732-4
Springer Science and Business Media LLC
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