Implementing a generative machine learning architecture to produce training data for a classification model
US12080380B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 27, 2021 |
| Grant date | Sep 3, 2024 |
| Priority date | — |
| Expiry date | Aug 27, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16B40/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Amino acid sequences of proteins can be produced using one or more generative machine learning architectures. The amino acid sequences produced by the one or more generative machine learning architectures can be used to train a classification model architecture. The classification model architecture can classify amino acid sequences according to a number of classifications. Individual classifications of the number of classifications can correspond to at least one of a structural feature of proteins, a range of values of a structural feature of proteins, a biophysical property of proteins, or a range of values of a biophysical property of proteins.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.