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Current methods for computationally predicting the locations and intron-exon structures of protein-coding genes in eukaryotic DNA are largely based on probabilistic, state-based generative models such as hidden Markov models and their various extensions. Unfortunately, little attention has been paid to the optimality of these models for the gene-parsing problem. Furthermore, as the prevalence of alternative splicing in human genes becomes more apparent, the "one gene, one parse" disciplinedoi:10.1007/978-3-540-71037-0_6 dblp:conf/kdecb/MajorosO06 fatcat:tud6gtajzjbddlbebm5llf2npm