Drugs and molecules, gene expression, genes and pathways classification, nutraceuticals, phenotypic profiles, in vivo activity and compound-protein interactions from multiple DBs.
Starting from an appropriate data frame containing chemistry, biology and assay information, built from SQL querying onto the selected ML DB, we can develop prediction and identification procedures. This section summarizes the subsequent procedures and algorithms employed. Whatever the route we take to identify pathways or targets of interest, or putative bioactive molecules, we can make them converge to confirm each other’s predictions.
The schema on the left attempts to illustrate how methodology described in the links below sustains an integrative prediction modelling.
