Figure 2.

A data science landscape for SARS-CoV-2 and COVID-19 studies. Many different technologies produce a large quantity of data related to patients at different scales (e.g. molecular data, medical images and clinical data and epidemiological data). The accumulation of this data is the pre-requisite for a substantial rise of data science approaches (e.g. deep-learning and classical data mining) that often integrate existing data stored in databases or a priori knowledge (e.g. domain experts or ontologies). Such approaches produce new information about molecular interactions, phylogenetic analysis, in silico design of drugs or healthcare management decisions. The output may guide the execution of novel experiments closing the loop of the whole process.