Alternative splicing is currently seen to explain the vast disparity between the number of predicted genes in the human genome and the highly diverse proteome. The mapping of expressed sequences tag (EST) consensus sequences derived from the GeneNest database onto the genome provides an efficient way of predicting exon-intron boundaries, gene structure and alternative splicing events. However, the alternative splicing events are obscured by a large number of putatively artificial exon boundaries arising due to genomic contamination or alignment errors. The current work describes a methodology to associate quality values to the predicted exon-intron boundaries. High quality exon-intron boundaries are used to predict constitutive and alternative splicing ranked by confidence values, aiming to facilitate large-scale analysis of alternative splicing and splicing in general.