| Summary: | 碩士 === 靜宜大學 === 資訊管理學系研究所 === 93 === Alternative splicing of a single pre-mRNA can give rise to different mRNA transcripts. Consequently, alternative splicing is an important mechanism for generating protein diversity from a single gene. Although alternative splicing is an important biological process, standard molecular biology techniques have only identified several hundred alternative splicing variants and create a bottleneck in terms of experimental validation.
In this thesis, we propose methods of obtaining models of weighted alternative splicing graphs and ways of generating all alternative splicing forms from a weighted alternative splicing graph.
Basically, the method uses the UniGene clusters of human Expressed Sequence Tags (ESTs) to identify alternative splicing sites. Furthermore, we utilize linear time algorithms that correctly produce all possible alternative splicing variants with their corresponding probabilities.
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