ABSTRACT
The amount of raw data has exponentially increased due to tools and technologies for analysis of biologic organisms (including viruses). The task now, therefore, is to have computational systems that allow the average researcher to calculate information to store, retrieve, visualize, and analyze data. Fortunately, the advancement of computer technology, particularly that relating to databases, has balanced continuous improvements to data-intensive biologic technologies. This research forms the foundation of many of the bioinformatics technologies that provide an overview of the different databases available for viruses and how they provide valuable information from the stored biologic data. The different tools associated with virus analysis are also discussed, accompanied by a summary of several online databases that contain general biologic and viral data. The chapter also features a case study on evaluating genome relationship between SARS-CoV-2 strains at different geolocations. © 2021 Elsevier Inc. All rights reserved.
ABSTRACT
COVID-19 is a global catastrophe affecting over 200 nations worldwide. The RT-PCR and antibody based detection assay are considered as a standard diagnostic method and are expensive, time-consuming with low sensitivity (40–80%) making it imperative to look for alternatives. COVID-19 patients display severe lung damage which can be spotted in chest X-ray and CT scan which can be analyzed by computational methods for confirmation of the disease. Apart from above techniques, we have discussed battery of computational intelligence tools like docking, molecular dynamics and quantum mechanics (QM), the novel biosensor based diagnostic tool has been developed. The biosensor involves hybridization of SARS-CoV-2 RNA with cDNA to form RNA (viral)–cDNA (probe) hybrid, with intercalation of transition metal Osmium-Ruthenium (II) redox probe that release electrons. The electrons generated by redox metal measured by respective electrodes and detect even miniscule quantities of viral-RNA in the sample. The computational methods support efficient measurement of interaction of redox probe with viral genetic material and intercalation of the Osmium-Ruthenium (II) redox probe between RNA-cDNA hybrid. The computational docking offers proof of concept with better sensitivity, speed and accuracy, by presenting stronger interaction of RNA–DNA hybrid with Osmium (II) redox probe as compared DNA-DNA hybrid in RT-PCR. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.