Human Full-Length Pre-mRNA Sequence Dataset for Computational Gene Prediction and Alternative Splicing Analysis

Introduction Computational gene prediction has recently become essential to identify all the genes from enormous genome sequences and to define their functions. However, gene prediction methods still show low specificity (45% at the exon level) [7]. Although computationally predicted data by automatic annotation system are growing rapidly, experimentally verified data provide the cornerstone for improvements of gene prediction. Because there is no guarantee that the predicted events occur in vivo. It has become important to discriminate experimentally verified data from computationally predicted data [5]. Aligning expressed sequence tags (ESTs)/mRNAs to the genomic sequences has been a practical approach to detect gene regions and to identify alternative splicing on a genomic scale. In previous studies EST-genome alignments were made using 90-93% sequence identity as threshold [2, 3, 4]. However, their low thresholds allow ESTs to incorrectly align with paralogous genes or pseudogene