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• W2671644384 abstract "Although high-throughput sequencing methods have been proposed to identify splicing branch points in the human genome, these methods can only detect a small fraction of the branch points subject to the sequencing depth, experimental cost and the expression level of the mRNA. An accurate computational model for branch point prediction is therefore an ongoing objective in human genome research.We here propose a novel branch point prediction algorithm that utilizes information on the branch point sequence and the polypyrimidine tract. Using experimentally validated data, we demonstrate that our proposed method outperforms existing methods. Availability and implementation: https://github.com/zhqingit/BPP.djguo@cuhk.edu.hk.Supplementary data are available at Bioinformatics online." @default.
• W2671644384 created "2017-06-30" @default.
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• W2671644384 date "2017-06-19" @default.
• W2671644384 modified "2023-09-30" @default.
• W2671644384 title "BPP: a sequence-based algorithm for branch point prediction" @default.
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• W2671644384 doi "https://doi.org/10.1093/bioinformatics/btx401" @default.
• W2671644384 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28633445" @default.
• W2671644384 hasPublicationYear "2017" @default.
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