ConvergeGEO™ is trained on over 1 trillion gene tokens and 100 million gene expression profiles, enabling deep understanding of gene regulation and expression across organisms. The architecture powers transcript optimization, 5’ and 3’ UTR optimization, and promoter optimization to enhance protein yield, stability, and manufacturability. ConvergeGEO™ supports expression system-specific design across CHO, HEK293, E. coli, Pichia, S. cerevisiae, and A. oryzae, delivering optimized constructs ready for experimental validation.
Input
Explainability & Output
A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.
2nd
Predictors
Explainability & Output
A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.
Output
Explainability & Output
A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.
