2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology
(IEEE CIBCB 2012)
Special Session on Computational Intelligence for Microarray Data Analysis

This Special Session on Computational Intelligence for Microarray Data Analysis will be held within the 9th IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, in San Diego, USA, May 9-12, 2012. This special session is organized by the Bioinformatics and Bioengineering Technical Committee (BBTC) of the IEEE Computational Intelligence Society (CIS). Please visit http://www.cibcb.org/2012 for more information.
Motivation:
Microarray data analysis is an important topic in bioinformatics and computational biology. As genes can be monitored synchronically by microarray technique, microarray data compile the expression levels of various genes over a set of biological samples, for example, different drug treatments or normal vs. cancer cell lines. To observe physiological or pathological procession, we can also measure gene expression over a series of time points. Important applications of microarray data include classification and prediction of various human diseases, clustering of gene patterns and regulatory mechanisms, selection of identified biomarkers, reconstruction of gene regulatory networks (GRNs). However, there are quite a few problems in microarray data analysis that challenge bioinformatics scientists, for example, data noise, missing value, high false positive rate, measurement uncertainty, data imprecision, high dimensionality, difficulty of mining temporal information, low accuracy of current GRN models, and expensive computational cost.
We believe that Computational intelligence (CI) can effectively address these challenging issues. We propose to tackle these problems using the following methods, but not limited to: (1) Neural networks and kernel based approaches can be used for classification, clustering, and gene selection; (2) Genetic and swarm intelligence algorithms can be used to search a discriminative subset of genes; (3) Modeling optimal GRNs is a NP-hard problem, and hence CI could be employed as alternative approaches to search good structures, given appropriate representations of the (dynamic) networks.
This special session is soliciting high-quality papers of original research and application papers that have not been published elsewhere and are not under consideration for publication elsewhere. All papers will be rigorously reviewed by at least 3 reviewers. Accepted papers will be published in the CIBCB 2012 proceedings (with ISBN number), included in the IEEE Xplore digital library, and indexed by EI/Compendex. This special session is of clear interest to the computational intelligence community, the biology communities, as well as the multilinear (tensor) algebra community.

Topics:

The topics of this special session include, but are not limited to:
* microarray time-series data analysis
* microarray DNA methylation data analysis
* clustering, biclusering, and triclustering of gene expression profiles
* clinical diagnosis and prognosis
* gene selection
* pathway analysis
* microarray visualization, image processing and data preprocessing
* modeling and reconstructing gene regulatory networks
* network based systems biology

Co-Organizers:

Dr. Yifeng Li
School of Computer Science
University of Windsor
Windsor, ON, N9B 3P4, Canada
Email: li11112c@uwindsor.ca

Dr. Chengpeng (Charlie) Bi
Division of Clinical Pharmacology
The Children's Mercy Hospitals and Clinics
Kansas City, MO 64108, USA
Email: cbi@cmh.edu

Dr. Sung-Bae Cho
Computer Science Department
Yonsei University
Seoul, 120-749, Korea
Email: sbcho@cs.yonsei.ac.kr

Dr. Kyung-Joong Kim
Department of Computer Engineering,
Sejong University
Seoul, 143-747, Korea
Email: kimkj@sejong.ac.kr

Dr. Alioune Ngom
School of Computer Science
University of Windsor
Windsor, ON, N9B 3P4, Canada
Email: angom@cs.uwindsor.ca