Predicting mutational function using machine learning

Keyphrases

• Machine Learning 100%
• Genetic Variation 100%
• Machine Learning Techniques 100%
• Computational Approach 100%
• Complex Disease 50%
• Aging 50%
• Human Subjects 50%
• Disease Risk 50%
• Prediction Accuracy 50%
• Heart Disease 50%
• Computational Model 50%
• Phenotypic Variation 50%
• Germline Variation 50%
• Human Genome 50%
• Human Individual 50%
• Somatic Cells 50%
• Diabetes Disease 50%
• Somatic mutation 50%
• Cancer Causes 50%
• Gene Expression Changes 50%
• Structural Alterations 50%
• High Abundance 50%
• Germline mutation 50%
• Mendelian Disease 50%
• Aging Characteristics 50%
• Change Risk 50%
• Classical Machine Learning 50%
• Deep Neural Network Algorithm 50%
• Age-related Illnesses 50%
• Prediction Potential 50%

Biochemistry, Genetics and Molecular Biology

• Genetic Variation 100%
• Germline 50%
• Structural Protein 50%
• Gene Expression 50%
• Human Genome 50%
• Somatic Mutation 50%
• Phenotypic Variation 50%
• Germline Mutation 50%
• Germ Cell 50%
• Somatic Cell 50%
• Homo sapiens 50%

Neuroscience

• Genetic Variation 100%
• Germ Cell 100%
• Neural Network 50%
• Gene Expression 50%
• Somatics 50%
• Somatic Cell 50%
• Structural Protein 50%