Posted Wed, Apr, 03,2013
Published today in Bioinformatics and Biology Insights is a new original research article by Bram Sebastian and Samuel E. Aggrey. Read more about this paper below:
Title
miR-Explore: Predicting MicroRNA Precursors by Class Grouping and Secondary Structure Positional Alignment
Abstract
MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expressions by targeting the mRNAs especially in the 3′UTR regions. The identification of miRNAs has been done by biological experiment and computational prediction. The computational prediction approach has been done using two major methods: comparative and noncomparative. The comparative method is dependent on the conservation of the miRNA sequences and secondary structure. The noncomparative method, on the other hand, does not rely on conservation. We hypothesized that each miRNA class has its own unique set of features; therefore, grouping miRNA by classes before using them as training data will improve sensitivity and specificity. The average sensitivity was 88.62% for miR-Explore, which relies on within miRNA class alignment, and 70.82% for miR-abela, which relies on global alignment. Compared with global alignment, grouping miRNA by classes yields a better sensitivity with very high specificity for pre-miRNA prediction even when a simple positional based secondary and primary structure alignment are used.
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Thu 08 Oct, 2015
Published This Week (5th - 9th October)Thu 08 Oct, 2015
Biomarker Insights Paper Endorsed by Editor in ChiefWed 07 Oct, 2015
Interview with Professor Jamie DaviesIt is an absolute pleasure serving as a peer reviewer for Libertas Academia. The review process was efficient and easy to navigate. I am looking forward to peer reviewing additional articles in the future.
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