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.

Abstract: This invention relates to methods and apparatus for determining the multi-dimensional topology of a substance (system) within a volume (space). A method according to a preferred embodiment of the invention comprises the steps of: acquiring a set of relative values for the density (scalar properties) of the volume, each value for a given location (point) within the volume; interpolating a set of functions to generate a continuous relative density for the volume; identifying critical points of the continuous relative density by using an eigenvector following method; and associating critical points with one another by following a gradient path of the continuous relative density between the critical points. The method is applicable to a wide range of data relating to fields such as crystallography, fluid dynamics, edge detection, and financial markets, to determine the topology of structures contained therein.

Abstract: This invention relates to methods and apparatus for determining the multi-dimensional topology of a substance (system) within a volume (space). A method according to a preferred embodiment of the invention comprises the steps of: acquiring a set of relative values for the density (scalar properties) of the volume, each value for a given location (point) within the volume; interpolating a set of functions to generate a continuous relative density for the volume; identifying critical points of the continuous relative density by using an eigenvector following method; and associating critical points with one another by following a gradient path of the continuous relative density between the critical points. The method is applicable to a wide range of data relating to fields such as crystallography, fluid dynamics, edge detection, and financial markets, to determine the topology of structures contained therein.

Abstract: This invention relates to methods and apparatus for determining the multi-dimensional topology of a substance (system) within a volume (space). A method according to a preferred embodiment of the invention comprises the steps of: acquiring a set of relative values for the density (scalar properties) of the volume, each value for a given location (point) within the volume; interpolating a set of functions to generate a continuous relative density for the volume; identifying critical points of the continuous relative density by using an eigenvector following method; and associating critical points with one another by following a gradient path of the continuous relative density between the critical points, The method is applicable to a wide range of data relating to fields such as crystallography, fluid dynamics, edge detection, and financial markets, to determine the topology of structures contained therein.