Omics data analysis and integration for COVID-19 patients - editorial.

Abstract

In the latest year, the SARS-CoV-2 virus has spread around the world leading to the explosion of the coronavirus disease 2019 (COVID-19) pandemic. Up to now over 514 000 000 patients with > 6 200 000 deaths have been reported. Since its rapid spread and high case fatality ratio, researchers have concentrated in exposing the origin, mutational tendency, pathogenesis and vaccine of the virus. Sequencing is producing large amounts of Omics data for SARS-CoV-2 virus and COVID-19 patients. For example, over 300 000 SARS-CoV-2 genomes were reported in GISAID since the first publication of the SARS-CoV-2 genome on 24 January 2020. Thousands of COVID-19 patients were sequenced for screening susceptible SNPs. Currently one of the major challenge is to mine casual molecules and phenotypes by integrating multi-level Omics data using system biology methods, which may expand our knowledge of curing COVID-19. This special issue aims to provide a comprehensive overview and innovative penetration, including but not limit to integrative methods and tools for analyzing multi-level Omics data, design of novel methods for exposing casual molecules and phenotypes of COVID-19 patients, design of novel methods for identifying novel drug targets, identification of molecular signatures of COVID-19 patients and identification of mutational tendency of SARS-CoV-2.