Abstract
Biclustering is a popular method which can reveal unknown genetic pathways. However, even though many algorithms have been suggested, no overwhelming algorithm has been suggested, due to its significant search space, until now. In this respect, several evolutionary algorithms tried to address this problem utilizing the powerful search capability of Evolutionary Computation (EC). However, most algorithms focused on exploiting the Mean Square Residue (MSR) measure which was proposed by Cheng and Church. The Order Preserving Sub-Matrix (OPSM) constraint was rarely considered even though it promises more biologically relevant biclusters than the MSR measure. The goal of this paper is to design an EC algorithm which ensures biologically significant biclusters by using the OPSM constraint and better biclusters than the original OPSM algorithm. We designed a novel encoding method and evolutionary operators suitable for the OPSM constraint. To efficiently explore the search space, we modulized our evolutionary algorithm and applied the co-evolution concept. Through a set of experiments, it was confirmed that our algorithm outperformed a representative EC biclustering algorithm based on CC and the original OPSM algorithm.
| Original language | English |
|---|---|
| Title of host publication | 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008 |
| DOIs | |
| Publication status | Published - 2008 Dec 1 |
| Event | 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008 - Athens, Greece Duration: 2008 Oct 8 → 2008 Oct 10 |
Other
| Other | 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008 |
|---|---|
| Country | Greece |
| City | Athens |
| Period | 08/10/8 → 08/10/10 |
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All Science Journal Classification (ASJC) codes
- Biotechnology
- Bioengineering
Cite this
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A novel evolutionary algorithm for bi-clustering of gene expression data based on the order preserving sub-matrix (OPSM) constraint. / Roh, Hongchan; Park, Sanghyun.
8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008. 2008. 4696685.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A novel evolutionary algorithm for bi-clustering of gene expression data based on the order preserving sub-matrix (OPSM) constraint
AU - Roh, Hongchan
AU - Park, Sanghyun
PY - 2008/12/1
Y1 - 2008/12/1
N2 - Biclustering is a popular method which can reveal unknown genetic pathways. However, even though many algorithms have been suggested, no overwhelming algorithm has been suggested, due to its significant search space, until now. In this respect, several evolutionary algorithms tried to address this problem utilizing the powerful search capability of Evolutionary Computation (EC). However, most algorithms focused on exploiting the Mean Square Residue (MSR) measure which was proposed by Cheng and Church. The Order Preserving Sub-Matrix (OPSM) constraint was rarely considered even though it promises more biologically relevant biclusters than the MSR measure. The goal of this paper is to design an EC algorithm which ensures biologically significant biclusters by using the OPSM constraint and better biclusters than the original OPSM algorithm. We designed a novel encoding method and evolutionary operators suitable for the OPSM constraint. To efficiently explore the search space, we modulized our evolutionary algorithm and applied the co-evolution concept. Through a set of experiments, it was confirmed that our algorithm outperformed a representative EC biclustering algorithm based on CC and the original OPSM algorithm.
AB - Biclustering is a popular method which can reveal unknown genetic pathways. However, even though many algorithms have been suggested, no overwhelming algorithm has been suggested, due to its significant search space, until now. In this respect, several evolutionary algorithms tried to address this problem utilizing the powerful search capability of Evolutionary Computation (EC). However, most algorithms focused on exploiting the Mean Square Residue (MSR) measure which was proposed by Cheng and Church. The Order Preserving Sub-Matrix (OPSM) constraint was rarely considered even though it promises more biologically relevant biclusters than the MSR measure. The goal of this paper is to design an EC algorithm which ensures biologically significant biclusters by using the OPSM constraint and better biclusters than the original OPSM algorithm. We designed a novel encoding method and evolutionary operators suitable for the OPSM constraint. To efficiently explore the search space, we modulized our evolutionary algorithm and applied the co-evolution concept. Through a set of experiments, it was confirmed that our algorithm outperformed a representative EC biclustering algorithm based on CC and the original OPSM algorithm.
UR - http://www.scopus.com/inward/record.url?scp=67549090422&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67549090422&partnerID=8YFLogxK
U2 - 10.1109/BIBE.2008.4696685
DO - 10.1109/BIBE.2008.4696685
M3 - Conference contribution
SN - 9781424428458
BT - 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008
ER -