Abstract: A method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a combination of a generative and a predictive model, training a phenotype prediction model based on experiential genotype vectors, training a genotype generation model based on sample genotype vectors, generating new genotype vectors, applying the phenotype prediction model to the new genotype vectors to generate scores, determining result genotypes based on a ranking of the available genotypes according to the scores, and generating a result based on the result genotypes, the result indicating one or more genetic constructs for testing.
Type:
Grant
Filed:
February 6, 2023
Date of Patent:
February 4, 2025
Assignee:
TESELAGEN BIOTECHNOLOGY INC.
Inventors:
Eduardo Abeliuk, Andrés Igor Pérez Manríquez, Juan Andrés Ramírez Neilson, Diego Francisco Valenzuela Iturra
Abstract: A method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a specialized prediction model, including receiving constraints, encoding genotype information in experimental data points corresponding to the constraints experiential genotype vectors, the experimental data points comprising the genotype information and phenotype information corresponding to the genotype information, training a phenotype prediction model based on the experiential genotype vectors, the corresponding phenotype information, and the one or more constraints, applying the phenotype prediction model to available genotypes corresponding to the constrains to generate scores, determining result genotypes based on a ranking of the available genotypes according to the scores, and generating, a result based on the result genotypes, the result indicating one or more genetic constructs for testing.
Type:
Grant
Filed:
December 23, 2019
Date of Patent:
April 4, 2023
Assignee:
TESELAGEN BIOTECHNOLOGY INC.
Inventors:
Eduardo Abeliuk, Juan Andrés Ramírez Neilson, Andrés Igor Pérez Manríquez, Diego Francisco Valenzuela Iturra
Abstract: A method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a combination of a generative and a predictive model, training a phenotype prediction model based on experiential genotype vectors, training a genotype generation model based on sample genotype vectors, generating new genotype vectors, applying the phenotype prediction model to the new genotype vectors to generate scores, determining result genotypes based on a ranking of the available genotypes according to the scores, and generating a result based on the result genotypes, the result indicating one or more genetic constructs for testing.
Type:
Grant
Filed:
April 26, 2021
Date of Patent:
February 7, 2023
Assignee:
TESELAGEN BIOTECHNOLOGY INC.
Inventors:
Eduardo Abeliuk, Andrés Igor Pérez Manríquez, Juan Andrés Ramírez Neilson, Diego Francisco Valenzuela Iturra