Here, the authors present COMEBin, a metagenomics binning method based on contrastive multi-view representation learning that uses data augmentation to generate multiple fragments (views) of each contig, resulting in high-quality embeddings of heterogeneous features. COMEBin outperforms state-of-the art binning methods, particularly in recovering near-complete genomes from real environmental samples.
- Ziye Wang
- Ronghui You
- Shanfeng Zhu
