Quantitative Analysis of Alternative Splicing Forms from EST Database

Alternative splicing of premessenger RNA is an important layer of gene expression regulation in eukaryotic cell. About 40-60% of human genes have alternative splice forms, suggesting that alternative splicing is one of the most significant components of the functional complexity of the human genome. Alternative splicing can produce variant proteins and expression patterns as different as the products of different genes. Despite the prevalence of alternative splicing, most alternative splicing forms have not been quantified [9]; still, identifying popular or useful alternative splicing forms remains an important but difficult task for biologists. In this paper, we propose and formulate linear programming models and use the popular linear programming solver to obtain the quantitative distributions of various alternative splicing forms. By aligning sequences of EST database to the genomic data, we identify locations of exons as well as the alternative splicing sites. To quantify these putative alternative splicing forms, we we choose segments in genome to count the EST number, and combine the information of EST and alternative splicing form by constructing the suitable linear programming model.