A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies.

ABSTRACT:

Background

Biologists aim to understand the genetic background of diseases, metabolic disorders or any other genetic condition. Microarrays are one of the main high-throughput technologies for collecting information about the behaviour of genetic information on different conditions. In order to analyse this data, clustering arises as one of the main techniques used, and it aims at finding groups of genes that have some criterion in common, like similar expression profile. However, the problem of finding groups is normally multi dimensional, making necessary to approach the clustering as a multi-objective problem where various cluster validity indexes are simultaneously optimised. They are usually based on criteria like compactness and separation, which may not be sufficient since t

SUBMITTER: Parraga-Alava J 

PROVIDER: S-EPMC6081857 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature