Evolutionary clustering algorithm
AssigneeKoninklijke Philips N.V.
InventorsNarayan Behera, Shruti Sinha, Rakesh Gupta, Ann Geoncy, Nevenka Dimitrova
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Abstract
The invention relates to selecting a set of candidate genes from a pool of genes. The method comprising receiving a set of gene data; arranging the set of gene data into a set of clusters with similar profiles by use of a clustering algorithm; and inputting the set of clusters into a genetic algorithm to select a set of candidate genes from the set of clusters. The method thus relates to hybrid between selection by clustering computation and selection by evolutionary computation. This hybrid is also referred to as an evolutionary clustering algorithm (ECA).
Claims20
A computer-implemented method for selecting a set of candidate genes from a pool of genes, the method comprising:
- receiving a set of gene data;
- arranging the set of gene data into a set of clusters with similar profiles by use of a clustering algorithm, wherein the clustering algorithm employs an interdependence redundancy measure as distance measure;
- and
- inputting the set of clusters into a genetic algorithm to select a set of candidate genes from the set of clusters, wherein in each evolution of the genetic algorithm, the genes are reassigned to clusters by first determining the gene of each cluster having the highest multiple interdependence redundancy and assigned other genes of the cluster in accordance with the genes having the highest interdependence redundancy.
A system for selecting a set of candidate genes from a pool of genes, the system comprising:
- a computing unit arranged to:
- receive a set of gene data;
- cluster the set of gene data into a set of clusters with similar profiles by use of a clustering algorithm;
- and
- evolve the set of clusters by a genetic algorithm to select a set of candidate genes from the set of clusters.
Dependencies are inferred from the claim text.