Special session jointly
sponsored by
and
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
-
Conference as "IJCNN 2008"
-
Session
Mode as "Special" and "Analysis of
high dimensional data in bioinformatics
(Organizers: Alexandru Floares, Francesco Masulli, Leif Peterson and
Gennady M.
Verkhivker)".
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