Deep Generative Models for Engineering Synthetic Microbes for Bioremediation

Deep Generative Models for Engineering Synthetic Microbes for Bioremediation

Authors- Vinod

Abstract--The increasing burden of environmental pollutants from industrial waste, plastic accumulation, and toxic chemical spills necessitates innovative and sustainable remediation strategies. Synthetic biology offers a powerful means to address this issue by enabling the design of microbes capable of degrading and neutralizing harmful substances. However, the design of such microbes is complicated by the vast combinatorial space of genetic elements and the complex behavior of biological systems. Deep generative models, a class of artificial intelligence techniques capable of producing novel biological sequences and pathways, provide a promising approach to accelerate and optimize the engineering of synthetic microbes for bioremediation. This research discusses how these models can support the generation of novel enzymes, regulatory elements, and whole-cell designs for improved environmental detoxification.

DOI: /10.61463/ijset.vol.13.issue2.433