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. 2016 Jul 22;60(8):4722–4733. doi: 10.1128/AAC.00075-16

TABLE 2.

Strong classification markers for the ciprofloxacin resistance data set identified by machine learning analysesa

Data set (CIPr vs. CIPs) Gene SNP positionb Product Fold no.
SNPs PA14_23260; gyrA 2015001 DNA gyrase subunit A 5
PA14_20440; phnN 1758114 Phosphonate transport ATP-binding protein 4
PA14_60790 5418859 Putative ABC transporter, ATP-binding protein 4
PA14_25600 2238920 Peptidase 3
PA14_34600 3074288 Putative glyceraldehyde-3-phosphate dehydrogenase 3
PA14_62810; secG 5604332 Preprotein translocase subunit 3
PA14_73360; gidB 6529928 Glucose-inhibited division protein B 3
PA14_08060 693759 Tail fiber assembly protein 3
Gene expression PA14_18480; algX Alginate biosynthesis protein AlgX 3
PA14_32290 Hypothetical protein 3
PA14_48950 Hypothetical protein 3
PA14_58410; opdP Glycine-glutamate dipeptide porin 3
PA14_59390 Hypothetical protein 3
PA14_62100; yedZ Sulfide oxidase subunit 3
a

The most frequently selected markers (a minimum of three outer training models [folds]) for differentiation between ciprofloxacin-susceptible and -resistant isolates are listed.

b

For the SNP data set, the genomic position of the mutation in the PA14 reference strain.