Genomic Variant Interpretation Machine Learning Pipeline

Develop a sophisticated Python-based machine learning pipeline for interpreting genetic variants using scikit-learn and Biopython. Create a system that integrates multiple data sources (genomic databases, clinical annotations, research literature) to classify genetic variants' potential pathogenicity. Implement ensemble learning techniques, provide explainable AI interpretations, and design a modular architecture supporting continuous model retraining.