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[PVS] [CIBCB] Special Session on Computational Intelligence forMicroarray Data Analysis



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