755-PlasMAAG: Reconstructing Plasmids Using AI
The paper introduces PlasMAAG, a novel computational tool designed to reconstruct plasmids and cellular genomes from complex metagenomic data. Unlike traditional methods that analyze samples individually, this framework utilizes assembly–alignment graphs (AAGs) to combine genetic information across multiple samples. By integrating contrastive learning and deep-learning-based binning, the tool effectively overcomes common obstacles such as fragmented data and genetic complexity. Benchmark testing demonstrates that PlasMAAG significantly outperforms existing technologies, recovering a higher…
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