Multivariate experiments applied to mammalian cells often produce lists of proteins/genes altered under treatment versus control conditions. Such lists can be projected onto prior knowledge of kinase-substrate interactions to infer the list of kinases associated with a specific protein list. By computing how the proportion of kinases, associated with a specific list of proteins/genes, deviates from an expected distribution, we can rank kinases and kinase families based on the likelihood that these kinases are functionally associated with regulating the cell under specific experimental conditions. Such analysis can assist in producing hypotheses that can explain how the kinome is involved in the maintenance of different cellular states and can be manipulated to modulate cells towards a desired phenotype.