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This folder contains the Python script and raw data.
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2025-12-24
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Additional file 4: of The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variantsâ but not always
Table S3. Significant predictive power of different subsets of resistance genes on antibiotic resistance genes not yet detected in pathogens (FARME database). (XLSX 11 kb)
Figshare2018-07-08 更新80
Figure 2. Comparison of ML Models in Predicting the Physicochemical Properties of Antibiotic Drugs Using R², MSE, MAE, and RMSE..docx
Comparison of ML Models in Predicting the Physicochemical Properties of Antibiotic Drugs
DataCite Commons2025-05-24 更新70
List of antimicrobial agents considered in the study.
For each of these antibiotics and each admission event, binary variables record whether the antibiotic: a) was currently prescribed, b) has been prescribed to the same patient in a previous admission,
Figshare2023-01-05 更新60
Supplementary Material 9
CD-HIT (Cluster Database at High Identity with Tolerance) is a widely used clustering algorithm that reduces redundancy in large genomic datasets. CD-HIT can group similar sequences or genomic feature
DataCite Commons2025-05-12 更新80
Whole Genome Sequencing of Escherichia coli bloodstream infections.
Goals of this study is to evaluate the ability of combination of three approaches: (1) patient epidemiologic characteristics ; (2) pathogen sequence type; and (3) resistance loci, in order to predict
NIAID Data Ecosystem60
