Article,
An Immune-Evolutionary Algorithm for Multiple Rearrangements of Gene Expression Data
Genetic Programming and Evolvable Machines, 5 (2): 157--179 (June 2004)
DOI: doi:10.1023/B:GENP.0000023686.59617.57
Abstract
Microarray technologies are employed to simultaneously
measure expression levels of thousands of genes. Data
obtained from such experiments allow inference of
individual gene functions, help to identify genes from
specific tissues, to analyse the behaviour of gene
expression levels under various environmental
conditions and under different cell cycle stages, and
to identify inappropriately transcribed genes and
several genetic diseases, among many other
applications. As thousands of genes may be involved in
a microarray experiment, computational tools for
organising and providing possible visualisations of the
genes and their relationships are crucial to the
understanding and analysis of the data. This work
proposes an algorithm based on artificial immune
systems for organizing gene expression data in order to
simultaneously reveal multiple features in large
amounts of data. A distinctive property of the proposed
algorithm is the ability to provide a diversified set
of high-quality rearrangements of the genes, opening up
the possibility of identifying various co-regulated
genes from representative graphical configurations of
the expression levels. This is a very useful approach
for biologists, because several coregulated genes may
exist under different conditions.
Tags
- algorithms
- algorithms,
- artificial
- clustering,
- evolutionary
- expression,
- gene
- genetic
- immune
- microarray,
- programming,
- systems,
