Lee Crawfurd, David K Evans, Susannah Hares, Justin Sandefur
Live tutoring calls did not improve learning during the COVID-19 pandemic in Sierra Leone
Journal of development economics
emergence antibiotic resistance bacteria important threat global health antibiotic resistance genes args key components define bacterial resistance spread different environments identification args particularly highthroughput sequencing data specimens stateoftheart method comprehensively monitoring spread evolution current computational methods identify args mainly rely alignmentbased sequence similarities known args approaches limited choice reference databases may potentially miss novel args similarity thresholds usually simple could accommodate variations across different gene families regions also difficult scale sequence data increasing study developed argnet deep neural network incorporates unsupervised learning autoencoder model identify args multiclass classification convolutional neural network classify args depend sequence alignment approach enables efficient discovery known novel args argnet accepts amino acid nucleotide sequences variable lengths partial 3050 aa 100150 nt sequences fulllength protein genes allowing application target sequencing metagenomic sequencing performance evaluation showed argnet outperformed deep learning models including deeparg hmdarg application scenarios especially quasinegative test analysis prediction consistency phylogenetic tree argnet reduced inference runtime 57 relative deeparg argnet flexible efficient accurate predicting broad range args sequencing data argnet freely available httpsgithubcomidbioinfoargnet online service provided httpsargnethkuhk video abstract