Semi-supervised prediction of protein subcellular localization using abstraction augmented Markov models

Keyphrases

• Markov Model 100%
• Unlabeled Data 85%
• Labeled Data 42%
• Co-training 28%
• Expectation Maximization 28%
• Training Base 28%
• High Cost 14%
• Protein Function 14%
• Subcellular Localization 14%
• Genome Annotation 14%
• Drug Discovery 14%
• Prediction Problems 14%
• Model-based Approach 14%
• Background Estimation 14%
• Protein Subcellular Localization Prediction 14%
• Supervised Machine Learning 14%
• Semi-supervised Training 14%
• Semi-supervised Method 14%

Computer Science

• Unlabeled Data 100%
• Annotation 16%
• Supervised Method 16%