Conference proceeding
Microarray Biclustering with Crowding Based MOACO
2009 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, pp 170-173
01 Jan 2009
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Biclustering methods allow us to identity genes with similar behavior with respect to different conditions. Ant Colony Optimization (A CO) algorithms have been shown to be effective problem solving strategies for Multiple Objective Optimization (MOO). Multiple Objective Ant colony optimization (MOACO) mainly focuses on solving the multiple objective combinatorial optimization problems. This paper incorporates crowding update technology into MOACOB and proposes a novel crowding based MOACO biclustering algorithm to mine biclusters from microarray dataset. Experimental results are shown for biclustering algorithm on two real gene expression dataset.
Metrics
11 Record Views
1 citations in Scopus
Details
- Title
- Microarray Biclustering with Crowding Based MOACO
- Creators
- Junwan Liu - Central South University of Forestry and TechnologyZhoujun Li - National University of Defense TechnologyXiaohua Hu - Drexel UniversityYiming Chen - National University of Defense TechnologyIEEE
- Publication Details
- 2009 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, pp 170-173
- Series
- IEEE International Conference on Bioinformatics and Biomedicine-BIBM
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- 09A105 / Hunan Provincial Education Department 0702613 / Central South University of Forestry Technology
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000275900200031
- Scopus ID
- 2-s2.0-74549191349
- Other Identifier
- 991019167670404721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Biochemical Research Methods
- Biotechnology & Applied Microbiology
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic