Abstract: Embodiments of the present invention are directed to a computer-implemented method for generating a list of genetic variants. A non-limiting example of the computer-implemented method includes receiving genetic and biological data. The exemplary method also includes generating data patterns from the genetic and biological data with data mining. The method also includes determining redescription distances between each of a plurality of data patterns. The method also includes generating computational homology filtrations from the redescription distances using a topological data analysis and homology groups including homology group elements based upon the computational homology filtrations. The method also includes generating a single nucleotide polymorphism combination list based upon the homology group elements and redescription clusters.

Abstract: Embodiments of the present invention are directed to a computer-implemented method for generating a list of genetic variants. A non-limiting example of the computer-implemented method includes receiving genetic and biological data. The exemplary method also includes generating data patterns from the genetic and biological data with data mining. The method also includes determining redescription distances between each of a plurality of data patterns. The method also includes generating computational homology filtrations from the redescription distances using a topological data analysis and homology groups including homology group elements based upon the computational homology filtrations. The method also includes generating a single nucleotide polymorphism combination list based upon the homology group elements and redescription clusters.

Abstract: A method in a data processing system for generating and storing in a database at least one descriptor vector and at least one reference frame for at least one region of a molecule includes a step of generating an entry including: i) a key derived from the at least one descriptor vector, wherein the key identifies the at least one region, and ii) a set of axes derived from property distribution information of the at least one region, the set of axes characterizing the at least one region. The method further includes steps of applying a mapping to the descriptor vector associated with the at least one region based on preselected criteria and storing the entry in a memory, wherein the key is associated with the entry such that the key indexes the entry for retrieval thereof.

Abstract: The method of the present invention transforms descriptor vectors that characterize items partitioned into groups into a space that discriminates between those groups in a well defined optimal sense. First data is generated that represents a differences between the groups of descriptor vectors. Second data is generated representing variation within the groups of descriptor vectors. A set of component vectors is then identified that maximizes an F distributed criterion function that measures differences of descriptor vectors between groups relative to variations of descriptor vectors within groups. A statistic is generated for subsets of the component vectors. For each particular subset of component vectors, a probability value for the statistic associated with the particular subset is calculated. The subset with the minimum probability value is selected. Finally, one or more of the descriptor vectors for the items are mapped to a space corresponding to the selected subset of component vectors.

Abstract: The method of the present invention transforms descriptor vectors that characterize molecular complexes partitioned into groups into a space that discriminates between those groups in a well defined optimal sense. First data is generated that represents a differences between the groups of descriptor vectors. Second data is generated representing variation within the groups of descriptor vectors. A set of component vectors is then identified that maximizes an F distributed criterion function that measures differences of desciptor vectors between groups relative to varations of descriptor vectors within groups. A statistic is generated for subsets of the component vectors. For each particular subset of component vectors, a probability value for the statistic associated with the particular subset is calculated. The subset with the minimum probability value is selected.