Metagenomics › Machine Learning Metagenome Assembly Research
Automated Quality Assessment and Parameter Optimization for Assembly Pipelines
Interns will develop machine learning systems that predict optimal assembly parameters and evaluate assembly quality metrics (N50, completeness, contamination) without requiring reference genomes. They will create automated decision-making tools that select the best assembly strategy for diverse metagenomic datasets based on sequencing characteristics.
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