This review is focused at exploring the strengths of modern technology driven data compiled in the areas of virus gene sequencing, virus protein structures and their implication to viral diagnosis and therapy. The information for virome analysis (viromics) is generated by the study of viral genomes (entire nucleotide sequence) and viral genes (coding for protein). Presently, the study of viral infectious diseases in terms of etiopathogenesis and development of newer therapeutics is undergoing rapid changes. Currently, viromics relies on deep sequencing, next generation sequencing (NGS) data and public domain databases like GenBank and unique virus specific databases. Two commonly used NGS platforms: Illumina and Ion Torrent, recommend maximum fragment lengths of about 300 and 400 nucleotides for analysis respectively. Direct detection of viruses in clinical samples is now evolving using these methods. Presently, there are a considerable number of good treatment options for HBV/HIV/HCV. These viruses however show development of drug resistance. The drug susceptibility regions of the genomes are sequenced and the prediction of drug resistance is now possible from 3 public domains available on the web. This has been made possible through advances in the technology with the advent of high throughput sequencing and meta-analysis through sophisticated and easy to use software and the use of high speed computers for bioinformatics. More recently NGS technology has been improved with single-molecule real-time sequencing. Here complete long reads can be obtained with less error overcoming a limitation of the NGS which is inherently prone to software anomalies that arise in the hands of personnel without adequate training. The development in understanding the viruses in terms of their genome, pathobiology, transcriptomics and molecular epidemiology constitutes viromics. It could be stated that these developments will bring about radical changes and advancement especially in the field of antiviral therapy and diagnostic virology.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5747850PMC
http://dx.doi.org/10.1007/s13337-017-0415-3DOI Listing

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