BacARscan (Bacterial Antibiotic Resistance scan) is an in-silico tool that can detect, predict and characterize antibiotic resistance genes (ARGs) in -omics datasets, including short sequencing, reads, and fragmented contigs. The data to build BacARscan is taken from (i) existing antibiotic resistance gene resources and primary databases (e.g. CARD, ARDB, LacED, Resfams etc.), (ii) UniProtKB and (iii) by comprehensive literature survey. All genes were first binned on the basis of their antibiotic inactivation profile. Genes in each bin are then divided into distinct cluster on the basis of their sequence homology. From each gene sequence cluster a profile HMM model is generated. Each profile HMM model is manually annotated and curated with its different properties namely, information and descriptions about the gene/protein name and their corresponding families; where particular gene/protein belongs, associated enzyme commission (EC) numbers, organism name, interactions and pathway information related with specific gene/protein, 3D structural information of each gene/protein, and their subcellular location, functions, resistance mechanism and gene ontology (cellular component, molecular function & biological process) as well as their UniProt accession number. Upon search BacARscan gives the alignment score and E-value of query sequence(s) to the profile HMM.