Identification of Novel COVID-19 Biomarkers by Multiple Feature Selection Strategies.

ABSTRACT: Coronavirus disease 2019 (COVID-19) arising from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a global pandemic since its first report in December 2019. So far, SARS-CoV-2 nucleic acid detection has been deemed as the golden standard of COVID-19 diagnosis. However, this detection method often leads to false negatives, thus triggering missed COVID-19 diagnosis. Therefore, it is urgent to find new biomarkers to increase the accuracy of COVID-19 diagnosis. To explore new biomarkers of COVID-19 in this study, expression profiles were firstly accessed from the GEO database. On this basis, 500 feature genes were screened by the minimum-redundancy maximum-relevancy (mRMR) feature selection method. Afterwards, the incremental feature selection (IFS) method was used

SUBMITTER: Zhang S 

PROVIDER: S-EPMC8485143 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature