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Research Frontiers in Deep Learning Metabolic Pathway Design

Using graph neural networks to design optimal metabolic pathways for bioproduction of chemicals and pharmaceuticals.

Neural Latent Spaces for Enzyme Function Prediction
Graph Neural Networks in Synthetic Pathway Optimization
Transformer Models for Metabolic Flux Prediction
Deep Learning in Cofactor Specificity and Selectivity
Attention Mechanisms for Multi-step Biosynthesis Design
Sequence-to-Pathway Generation Using Language Models
Deep Generative Models for Novel Enzyme Discovery
Learned Representations of Metabolic Bottlenecks
Neural Networks Bridging Genotype to Metabolic Output
Deep Learning for Cross-Organism Pathway Portability

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