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  "Description": "Utilizing a combination of machine learning models (Random\nForest, Naive Bayes, K-Nearest Neighbor, Support Vector\nMachines, Extreme Gradient Boosting, and Linear Discriminant\nAnalysis) and a deep Artificial Neural Network model,\n'MBMethPred' can predict medulloblastoma subgroups, including\nwingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4 from\nDNA methylation beta values. See Sharif Rahmani E, Lawarde A,\nLingasamy P, Moreno SV, Salumets A and Modhukur V (2023),\nMBMethPred: a computational framework for the accurate\nclassification of childhood medulloblastoma subgroups using\ndata integration and AI-based approaches. Front. Genet.\n14:1233657. <doi: 10.3389/fgene.2023.1233657> for more details.",
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