An improved binary particle swarm optimisation for gene selection in classifying cancer classes
The application of microarray data for cancer classification has recently gained in popularity. The main problem that needs to be addressed is the selection of a smaller subset of genes from the thousands of genes in the data that contributes to a disease. This selection process is difficult because...
Saved in:
Main Authors: | Mohamad, Mohd. Saberi, Zainal, Anazida, Deris, Safa'ai |
---|---|
Format: | Book Section |
Published: |
Springer
2009
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/14441/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
by: Mohamad, Mohd. Saberi, et al.
Published: (2013) -
Particle swarm optimization for gene selection in classifying cancer classes
by: Mohamad, Mohd. Saberi, et al.
Published: (2009) -
An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
by: Mohd Saberi, Mohamad, et al.
Published: (2013) -
A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
by: Mohamad, Mohd. Saberi, et al.
Published: (2008) -
An improved binary particle swarm optimization algorithm for genes selection and classification of colon cancer data
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)