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Secondary Metabolism

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IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

mBio
UNLABELLED: In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In...

Fruit-In-Sight: A deep learning-based framework for secondary metabolite class prediction using fruit and leaf images.

PloS one
Fruits produce a wide variety of secondary metabolites of great economic value. Analytical measurement of the metabolites is tedious, time-consuming, and expensive. Additionally, metabolite concentrations vary greatly from tree to tree, making it dif...

Optimization of fungal secondary metabolites production via response surface methodology coupled with multi-parameter optimized artificial neural network model.

Bioresource technology
Filamentous fungi's secondary metabolites (SMs) possess significant application owing to their distinct structure and diverse bioactivities, yet their restricted yield levels often hinder further research and application. The study developed a respon...

Machine-Learning Analysis of Streptomyces coelicolor Transcriptomes Reveals a Transcription Regulatory Network Encompassing Biosynthetic Gene Clusters.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Streptomyces produces diverse secondary metabolites of biopharmaceutical importance, yet the rate of biosynthesis of these metabolites is often hampered by complex transcriptional regulation. Therefore, a fundamental understanding of transcriptional ...

Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their Validation.

Journal of chemical information and modeling
The need for new antidiabetic drugs is evident, considering the ongoing global burden of type-2 diabetes mellitus despite notable progress in drug discovery from laboratory research to clinical application. This study aimed to build machine learning ...

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...