ABSTRACT
The coronavirus disease 2019 (COVID-19) outbreak due to the novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been classified as a pandemic disease by the World Health Organization on the 12th March 2020. This world-wide crisis created an urgent need to identify effective countermeasures against SARS-CoV-2. In silico methods, artificial intelligence and bioinformatics analysis pipelines provide effective and useful infrastructure for comprehensive interrogation and interpretation of available data, helping to find biomarkers, explainable models and eventually cures. One class of such tools, pathway enrichment analysis (PEA) methods, helps researchers to find possible key targets present in biological pathways of host cells that are targeted by SARS-CoV-2. Since many software tools are available, it is not easy for non-computational users to choose the best one for their needs. In this paper, we highlight how to choose the most suitable PEA method based on the type of COVID-19 data to analyze. We aim to provide a comprehensive overview of PEA techniques and the tools that implement them.
ABSTRACT
The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses.