A novel deep contrastive convolutional autoencoder based binning approach for taxonomic independent metagenomics data
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13562-024-00911-2.pdf
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5. Herath D, Tang SL, Tandon K, Ackland D, Halgamuge SK (2017) CoMet: a workflow using contig coverage and composition for binning a metagenomic sample with high Precision. BMC Bioinformatics 18(16):161–172
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