The concept of synthetic lifeforms defined through digital genetic code represents a shift in contemporary biology, where living systems are no longer seen only as products of natural evolution but increasingly as programmable and computationally engineered entities whose properties can be encoded and optimized through algorithmic frameworks that integrate biological modeling, systems theory, and machine learning, enabling virtual designs to be refined before laboratory synthesis. This interdisciplinary domain emerges from synthetic biology, computational genomics, artificial intelligence, and systems neuroscience, forming a framework where biological systems are treated as information-processing architectures that can be modeled in silico through gene networks, protein interactions, and metabolic pathways, enabling simulation of organism behavior before experimental implementation and improving predictive accuracy in molecular engineering. At the molecular regulatory level, ...