Splice Site Prediction via Computational Segmentation

The patent segments the pre-mRNA sequence into distinct regions (exons, introns, splice sites) and applies specific computational analyses to each segment. The method divides the prediction task into multiple stages: initial sequence analysis, splice site identification, intron/exon boundary determination, and validation against known databases. This segmentation allows each component to be optimized independently, improving overall accuracy without requiring a single overly complex algorithm.

The patent employs preliminary action by first gathering and preprocessing reference data from known splice sites and intron/exon boundaries before performing the actual prediction. The method pre-establishes criteria for splice site recognition, pre-identifies conserved sequences, and pre-validates prediction algorithms against training datasets. This preliminary preparation creates a robust framework that enhances prediction accuracy while keeping the actual prediction process relatively simple.

The patent applies local quality by focusing verification efforts on specific critical regions rather than uniformly analyzing the entire sequence. The method concentrates computational resources on splice site regions, exon-intron boundaries, and conserved sequences where accuracy is most critical. Less critical regions receive minimal or no verification, optimizing the balance between reliability and time consumption by applying quality control where it matters most.

The patent implements partial action by performing verification only on predictions that meet certain confidence thresholds or exhibit specific characteristics. High-confidence predictions from initial analysis may skip extensive verification, while low-confidence or ambiguous cases receive full verification scrutiny. This selective verification approach maintains reliability for critical predictions while reducing overall time investment.

The patent merges multiple verification methods into a unified computational pipeline that automatically performs sequence analysis, splice site prediction, intron/exon identification, and database verification in a single integrated process. The method combines homology searching, conserved sequence analysis, statistical prediction, and experimental validation criteria into one cohesive workflow, maintaining high annotation precision while simplifying user operation through automation.

The patent implements self-service by designing the system to automatically perform all verification steps without requiring manual intervention at each stage. The computational method self-validates predictions by comparing against multiple databases, self-corrects errors through iterative refinement, and self-documented results with confidence scores. This automation maintains high precision while greatly improving ease of operation, as users simply need to input the sequence and receive comprehensive results.