Abstract: A method, system, computer program selecting attribute sets of characterizing attributes of an object, selecting an attribute set of attributes of interest, assigning a likelihood for each characterized attribute set that the attribute set occurs when the attribute set of interest occurs (each likelihood determined using Bayesian computable classifiers on a dataset of attributes for actual samples), comparing each assigned likelihood against likelihood thresholds, and reporting the assigned likelihoods of the characterizing attribute set based on the likelihood thresholds. Markers may be identified for diagnosis and prognosis. Characterizing attributes may be gene expression levels and the attribute of interest may be drug sensitivity level, drug dose (absolute concentration or dose relative to some standard dose), dose of drug which causes half-maximal cellular growth rate, or logarithm base 10 (dose) where dose is the dose which yields half-maximal total cell mass accumulating.