Special session jointly sponsored by

SIG on Bioinformatics of the International Neural Network Society (INNS)

and


International Society for Computational Biology (ISCB)

on

Analysis of High Dimensional Data in Bioinformatics

at

IEEE 2008 World Congress on Computational Intelligence (WCCI 2008) 
International Joint Conference on Neural Networks (IJCNN 2008)

Hong Kong Convention and Exhibition Centre, June 3, 9:30 -11:30, Room 405, 2008

http://www.wcci2008.org/

  



CALL FOR PAPERS

Description and Scope:

The body of information surrounding molecular and genomic experiments and clinical investigations is rapidly growing as the magnitude and rate of applications involving large-scale high-throughput technologies are ever-increasing. Bioinformatic data mining efforts now range from more recent methods including microRNA target identification and protein structure prediction to classical methods such as RBF and ANN classification of DNA microarray gene expression data. Data fusion and integration are also gaining considerable attention for mixing signals, features, images, and text data from multiple sensors together in order to understand influences of data components on early detection and diagnosis of disease. Altogether, bioinformatics has become a very promising multidisciplinary research topic in the life sciences because results provide new insights for interpretation and establish new leads for deeper understanding.

Bioinformatics data sets often show a high dimensionality, and, as a consequence, data are sparse. Even after feature reduction, usually, one is left still with hundreds of dimensions per object, which are significant for the data mining task. As a consequence, in those conditions many machine learning algorithms are prone to give unsatisfactory results (curse of dimensionality problem). This is one of the most challenging problems when we design Computational Intelligence and Machine Learning algorithms for the analysis of bioinformatic data sets (for clustering, text mining, signal and image processing, data visualization, etc.).
This session will take stock in new bioinformatic data mining developments for the analysis of high dimensional data in general, and Neural Network methods in particular.

Topics:

We welcome papers which present novel algorithms or refined classical methods for the analysis of high dimensional bioinformatic data sets. The range of topics includes but is not limited to:

*       Data integration and fusion
*       Ensemble techniques
*       Biological sequence identification
*       DNA/CGH/SNP/miRNA arrays
*       Gene regulatory and ontology networks
*       Protein-protein, protein-small molecule interactions
*       Protein structure prediction
*       Cellular metabolism and signaling
*       Pharmacogenomics and pharmacodynamics
*       Metabolic pathways
*       Signal processing
*       Unsupervised and supervised classification
*       Imaging/data visualization
*       Text mining methods
*       Biomarker selection

Organizers:

Alexandru Floares (1), Francesco Masulli (2), Leif Peterson (3) and Gennady M. Verkhivker (4)

(1) Department of Artificial Intelligence
Oncological Institute Cluj-Napoca
400015 Str. Republicii, Nr. 34-36, Cluj-Napoca Romania
E-mail: alexandru.floares <at> iocn.ro

(2) DISI Dept. Computer and Information Sciences
University of Genova
Via Dodecaneso 35, 16146 Genoa, Italy
E-mail: masulli <at> disi.unige.it

(3) Center for Biostatistics
The Methodist Hospital Research Institute
6565 Fannin Street, MGJ6-031, Houston, Texas  77030  USA
E-mail: lepeterson <at> tmhs.org

(4) Department of Pharmaceutical Chemistry
School of Pharmacy,
Center for Bioinformatics
The University of Kansas USA
and
Department of Pharmacology,
University of California San Diego USA
E-mail: verk <at> ku.edu
E-mail: gverkhiv <at> ucsd.edu

Technical Committee:

Anne M. Denton, Dept. Computer Science, North Dakota State University, Fargo, ND, USA
Carlotta Domeniconi, Dept. Information and Software Engineering, George Mason University, Fairfax, VA, USA
Emmanuel Ifeachor, University of Plymouth, UK
Ioannis A. Kakadiaris, University of Houston, Houston, TX, USA
Mark A. Kon, Department of Mathematics and Statistics, Boston University, Boston, MA, USA
Tianming Liu, Methodist Hospital Research Institute, Houston, TX, USA
Erzsebet Merenyi, Dept. Electrical and Computer Engineering, Rice University, Houston, TX, USA
David A. Pelta, Dept. of Computer Science and A.I., University of Granada, Granada, SPAIN
Giuseppe Russo, Sbarro Inst. for Cancer Research and Molecular Medicine, Temple University, Philadelphia, PA, USA
Guido Sanguinetti, Department of Computer Science, University of Sheffield, Sheffield, UK
Udo Seiffert, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
Roberto Tagliaferri, DMI, Università di Salerno, Fisciano, Italy
Marina Vannucci, Department of Statistics, Rice University, Houston, TX, USA

Important deadlines:

December 15, 2007

Paper submission deadline  (&)

February 1, 2008

Author notification of acceptance or rejection

March 1, 2008

Deadline for final paper submission


(&) Late submissions after December 15, 2007 and before January 1, 2008 may be considered only if time permits for review.


Paper submission:

At http://www.wcci2008.org/submission.htm you'll find the Instruction for Authors and the link to the IJCNN submission site.  

While submitting,  select 

Program:

09:30 Text-mining Protein-protein Interaction Corpus Using Concept Clustering to Identify Intermittency (NN0973) - Leif E. Peterson, The Methodist Hospital Research Institute, USA; Matthew A. Coleman, Lawrence Livermore National Laboratory, USA

09:50 Automatic Inferring Drug Gene Regulatory Networks with Missing Information Using Neural Networks and Genetic Programming (NN0852) - Alexandru Floares, IOCN & SAIA, Romania

10:10 A Novel Strategy for the Structure-based Drug Design of Heat Shock Protein 90 Inhibitors (NN0415) - Omix Yu-Chian Chen, China Medical University, Taiwan; Guan-Wen Chen, China Medical University, Taiwan; Winston Yu-Chen Chen, China Medical University, Taiwan

10:30 Robust Experimental Design and Feature Selection in Signal Transduction Pathway Modeling (NN0503) - Fei He, The University of Manchester, United Kingdom; Martin Brown, The University of Manchester, United Kingdom; Hong Yue, University of Strathclyde, United Kingdom; Lam Fat Yeung, City University of Hong Kong, Hong Kong

10:50 Pharmacoinformatics Approach to the Discovery of Novel Selective Cox-2 Inhibitors by in Silico Virtual Screening (NN0426) - Omix Yu-Chian Chen, Department of Biological Science and Technology, China Medical University, Taiwan

11:10 On the Complexity - Sensitivity Trade-off for the Nf-kb Pathway Modeling (NN1039) - Fei He, The University of Manchester, United Kingdom; Martin Brown, The University of Manchester, United Kingdom; Lam Fat Yeung, City University of Hong Kong, Hong Kong




Last updated 28/4/2008