AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A trade-off-aware framework is proposed that links causal-allele identification, mechanism-matched editing, quantitative allele design, multidimensional phenotyping, and validation across generations, genetic backgrounds, and production-relevant environments that can guide the development of balanced, breeding-ready to...
This study defines effective multiplex target combinations for ultra-high oleic, low-saturated soybean by simultaneously targeting fatty acid desaturase 2 (FAD2) and fatty acyl-ACP thioesterase B (FATB) gene families using CRISPR/Cas9.
An integrated AI-to-field framework that connects target discovery, editability prediction, DNA-free editing, regeneration reprogramming, phenotypic validation, and breeding deployment into a unified soybean improvement pipeline is proposed.
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