AIMC Topic: Biosynthetic Pathways

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Molecular insights fast-tracked: AI in biosynthetic pathway research.

Natural product reports
Covering: 2000 to 2025This review explores the potential of artificial intelligence (AI) in addressing challenges and accelerating molecular insights in biosynthetic pathway research, which is crucial for developing bioactive natural products with ap...

Deciphering the biosynthetic potential of microbial genomes using a BGC language processing neural network model.

Nucleic acids research
Biosynthetic gene clusters (BGCs), key in synthesizing microbial secondary metabolites, are mostly hidden in microbial genomes and metagenomes. To unearth this vast potential, we present BGC-Prophet, a transformer-based language model for BGC predict...

Deep learning in template-free de novo biosynthetic pathway design of natural products.

Briefings in bioinformatics
Natural products (NPs) are indispensable in drug development, particularly in combating infections, cancer, and neurodegenerative diseases. However, their limited availability poses significant challenges. Template-free de novo biosynthetic pathway d...

The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability.

Natural product reports
Covering: up to the end of 2020. The machine learning field can be defined as the study and application of algorithms that perform classification and prediction tasks through pattern recognition instead of explicitly defined rules. Among other areas,...