Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39063
Title: Recognition of polyadenylation sites from Arabidopsis genomic sequences.
Authors: Koh, C.H.
Wong, L. 
Issue Date: 2007
Source: Koh, C.H.,Wong, L. (2007). Recognition of polyadenylation sites from Arabidopsis genomic sequences.. Genome informatics. International Conference on Genome Informatics 19 : 73-82. ScholarBank@NUS Repository.
Abstract: A polyadenine tail is found at the 3' end of nearly every fully processed eukaryotic mRNA and has been suggested to influence virtually all aspects of mRNA metabolism. The ability to predict polyadenylation site will allow us to define gene boundaries, predict number of genes present in a particular gene locus and perhaps better understand mRNA metabolism. To this end, we built an arabidopsis polyadenylation prediction model. The prediction model uses a machine learning method which consists of four sequential steps: feature generation, feature selection, feature integration and cascade classifier. We have tested our model on public datasets and achieved more than 97% sensitivity and specificity. We have also directly compared with another arabidopsis prediction model, PASS 1.0, and have achieved better results.
Source Title: Genome informatics. International Conference on Genome Informatics
URI: http://scholarbank.nus.edu.sg/handle/10635/39063
ISSN: 09199454
Appears in Collections:Staff Publications

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