Chlorociboria aeruginosa

A Deep Learning and Explainable AI-Based Approach for the Classification of Discomycetes Species

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Researchers developed an artificial intelligence system to automatically identify 14 different types of cup fungi (Discomycetes) from photographs. Using a method called EfficientNet combined with explainable AI, the system achieved 97% accuracy in species identification. The technology could help scientists quickly and accurately catalog fungal biodiversity for conservation efforts and ecological studies without requiring expert mycologists to examine every specimen.

Identification of a Biosynthetic Gene Cluster for the Production of the Blue-Green Pigment Xylindein by the Fungus Chlorociboria aeruginascens

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Scientists discovered the genetic instructions that allow certain fungi to produce xylindein, a beautiful blue-green pigment found in stained wood. By analyzing fungal genomes and studying gene activity, they identified nine genes working together to create this valuable compound, which has uses in textiles and electronics. While attempts to produce xylindein in laboratory yeasts were unsuccessful, their work successfully produced a related pigment and opens new pathways for understanding xylindein production.

Fungal Species: Chlorociboria aeruginosa

A Deep Learning and Explainable AI-Based Approach for the Classification of Discomycetes Species

Identification of a Biosynthetic Gene Cluster for the Production of the Blue-Green Pigment Xylindein by the Fungus Chlorociboria aeruginascens