Identification of the expressome by machine learning on omics data

Keyphrases

• Machine Learning 100%
• DNA Methylation Pattern 100%
• Omics Data 100%
• Inbred Lines 100%
• Protein-coding Genes 100%
• Gene Set 100%
• Expressome 100%
• Proteomics 50%
• Redundancy 50%
• Transposable Elements 50%
• Functional Genes 50%
• Transcriptomics 50%
• Plant Genome 50%
• Maize Inbred Lines 50%
• Chromatin 50%
• Promoter Methylation 50%
• Expressed Genes 50%
• Whole Genome Duplication 50%
• Pseudogene 50%
• Gene Fragments 50%
• Training Data 50%
• Histone Modification 50%
• Epigenetic Marks 50%
• Reference Genome 50%
• Random Forest Algorithm 50%
• Gene Methylation 50%
• Gene Body 50%

Biochemistry, Genetics and Molecular Biology

• Methylation 100%
• Inbred Strain 100%
• DNA Methylation 100%
• Tamsulosin 100%
• Epigenetics 50%
• RNA 50%
• Transposable Element 50%
• Pseudogene 50%
• Histone Modification 50%
• Proteomics 50%
• Plant Genome 50%
• Transcriptomics 50%
• Promoter Region 50%
• Random Forest 50%