Data · dataset · 2024
Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes
Listed in Teesside University Research Data Repository
This dataset contains the following materials: 1.
Description
ZIP file of txt files. PATRIC Genome IDs and AMR phenotypes, with '1' indicating resistance and '0' indicating susceptibility, for 78 single-species-antibiotic datasets. 2.
ZIP file of JSON files. 223 (78+67+78) sets of random folds, phylogeny-aware folds, and homology-aware folds for 78 single-species-antibiotic datasets. Nine sets of homology-aware folds for nine multi-antibiotic datasets, each corresponding to one of nine species. A set of homology-aware folds for evaluating Aytan-Aktug control multi-species model and cross-species model.
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Nine sets of homology-aware folds for evaluating the Aytan-Aktug leave-one-species-out cross-species model. 3. ZIP file of PDF files. Phylogenetic trees generated by Geno2Pheno for 10 species (including 67 species-antibiotic combinations), annotated with phenotypes and the cross-validation folds for phylogeny-aware and random folds, respectively.
Links
Where it is published
- DOI doi.org/10.17632/6vc2msmsxj.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/6vc2msmsxj.2 | 7 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:310509 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Genomics'] |
| concepts[field].anzsrc:group:3102 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Computational Biology'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |