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Comparison between ribosomal assembly and machine learning tools for microbial identification of organisms with different characteristics

<p><strong>DNABERT+DeLUCS_notebooks.zip </strong></p> <ul> <li>Code notebooks for running DNABERT and DeLUCS</li> </ul> <p>&nbsp;</p> <p><strong>images-20230519T015235Z-001.zip </strong></p> <ul> <li>Heatmaps</li> <li>Factor plots</li> </ul> <p>&nbsp;</p> <p><strong>Data-20230518T191203Z-003.zip </strong></p> <ul> <li>MBARC and Hot Springs datasets <ul> <li>Reference genomes</li> <li>16S sequences (barrnap)</li> </ul> </li> </ul> <p>&nbsp;</p> <p><strong>hot-springs-reads.gz </strong></p> <ul> <li>Reads data for Hot Springs dataset</li> </ul> <p>&nbsp;</p> <p><strong>mbarc-reads-download.txt</strong></p> <ul> <li>Reads data for MBARC dataset <ul> <li>Link to download from NCBI</li> </ul> </li> </ul> <p>&nbsp;</p> <p><strong>assemblies.zip</strong></p> <ul> <li>Megahit and MetaSPAdes assemblies for both MBARC and Hot Springs</li> </ul>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0