Splicing site classification using neural networks
US12165742B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 29, 2023 |
| Grant date | Dec 10, 2024 |
| Priority date | — |
| Expiry date | Sep 29, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/24
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The technology disclosed relates to splice site prediction and aberrant splicing detection. In particular, it relates to a splice site predictor that includes a convolutional neural network trained on training examples of donor splice sites, acceptor splice sites, and non-splicing sites. An input stage of the convolutional neural network feeds an input sequence of nucleotides for evaluation of target nucleotides in the input sequence. An output stage of the convolutional neural network translates analysis by the convolutional neural network into classification scores for likelihoods that each of the target nucleotides is a donor splice site, an acceptor splice site, and a non-splicing site.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.