Article

Random forest machine-learning algorithm classifies white- and brown-rot fungi according to the number of Carbohydrate-Active enZyme genes

2024-03-17

Abstract excerpt

Wood-rotting fungi play an important role in the global carbon cycle because they are only known organisms that digest wood, the largest carbon stock in nature. In the present study, we used linear discriminant analysis and random forest (RF) machine learning algorithms to predict white- or brown-rot decay modes from the numbers of genes encoding Carbohydrate-Active enZymes (CAZymes) with over 98% accuracy. Unlike...

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Literature Corpus work: 41286fdd-45b8-5191-bfc0-e4f14ba0f44e
DOI: 10.1101/2024.03.15.585254

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Random forest machine-learning algorithm classifies white- and brown-rot fungi according to the number of Carbohydrate-Active enZyme genesDOI 10.1101/2024.03.15.585254Read

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