BPP: a sequence-based algorithm for branch point prediction
Motivation 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. Results We here propose a novel branch
point prediction algorithm that utilizes information on the branch point sequence and the …
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. Results We here propose a novel branch
point prediction algorithm that utilizes information on the branch point sequence and the …
Motivation
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.
Results
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.
Supplementary information
Supplementary data are available at Bioinformatics online.
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