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From:
Mario Cannataro <[log in to unmask]>
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Date:
Wed, 16 Jun 2010 00:44:14 +0200
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       I apologize for any cross-posting of this announcement.
=====================================================================
                23rd IEEE International Symposium on
                  COMPUTER-BASED MEDICAL SYSTEMS
                         Perth, Australia,
                        12-15 October 2010

     5th Special Track Computational Proteomics and Genomics:
                   Data Management and Analysis
             http://staff.icar.cnr.it/cannataro/cbms2010
=====================================================================
* * * CALL FOR PAPERS - EXtended Deadline June 24, 2010 * * *
=====================================================================

Genomics is the study of the genome, i.e. the whole hereditary information
of an organism that is encoded in the DNA (or, for some viruses, RNA).
Investigation of single genes, their functions and roles is becoming
common practice in today's medical and biological research. Genome-wide
sequencing projects have been completed for many organisms, including Homo
Sapiens.

Currently thousands of genes have been sequenced but still wait for any
functional information to be assigned to them: this suggests that current
comprehension of most biological and pathological processes is by far
incomplete. As a consequence, new technological platforms that exploit the
genome sequence information to explore gene function in a systematic way
are evolving at an incredibly high pace, e.g. microarray.

Application of the microarray technology has unveiled its enormous
potential as a diagnostic support to clinical management. Recent works
exploited gene expression profiling of tumor samples to define sets of
genes (signatures) whose expression correlates, positively or negatively,
with specific clinical features, such survival and response to therapy.
Other types of massive datasets currently generated in genomics and
projects include: protein expression levels measured by proteomics
screenings; protein-protein interaction datasets in various organisms;
protein structure data; genomic sequencing of additional organisms,
comparative genomics; sequence polymorphisms in human populations,
mutational analysis in human cancer and in hereditary diseases.

Proteomics is a fastly developing area of biochemical investigation and
regards the study of the proteins expressed in an organism or a cell.
Proteomics studies include: protein identification and quantification,
structural genomics, protein-to-protein interaction, post-translational
modifications, and so on. In medical studies, the basic aim of proteomic
analysis is the identification of specific protein patterns from cells,
tissues and biological fluids related to physiological or pathological
conditions (biomarker discovery). It provides a different view as compared
to gene expression profiling, which does not evaluate
post-transcriptional, post-translational modifications as well as protein
compartimentalization and half-life changes (for instance ubiquitination
and proteasome-driven degradation). All these characteristics make the
protein profile much more complex but more informative compared to gene
expression profiling.

Several approaches have been used to perform proteomic analysis; among
them, technologies based on Mass Spectrometry (MS) have revolutionized
proteomics and are heavily used to make high-throughput measurements for
identifying macromolecules in a specific compound. Some recent studies
based on mass spectrometry, conducted at the National Institutes of
Health, USA, have identified in biological samples cluster patterns that
completely segregated ovarian cancer from non-cancer. These results,
characterized by a high degree of sensitivity and specificity, represent
an extraordinary step forward in the early detection and diagnosis of
ovarian cancer and justify a prospective population-based assessment of
proteomic pattern technology as a screening tool for all stages of ovarian
cancer in high-risk and general populations. Similar studies performed on
different types of neoplastic diseases have confirmed the importance of
identification of “molecular profiles or signatures” (either at RNA or
protein level) as a powerful tool for innovative diagnostic and
therapeutic approaches.

Computational Proteomics is about the computational methods, algorithms,
databases, and methodologies used to manage, analyze and interpret the
data produced in proteomics experiments. The broad application of
proteomics in different biological and medical fields, as well as the
increasing resolution and precision offered by technological platforms,
make the analysis of proteomics experiments difficult and error prone
without efficient algorithms and easy-to-use tools. This is especially
true in Mass Spectrometry-based high-throughput proteomics, where the
production of huge datasets is coupled with the need of on-the-fly data
analysis.

The seamless integration of genomic, proteomics and clinical data, and the
semantic interoperation between bioinformatics tools and health management
systems, are first steps toward the so-called “Genomic Medicine”, i.e. the
combined use of genomics, proteomics, and clinical data to improve
healthcare. Future Electronic Patient Records should allow the integration
of genomic and proteomic data, while bioinformatics tools and databases
used for genomics and proteomics studies should be able to furnish input
to clinical practice, enabling the so called “from-bench-to-bed” paradigm.

This Workshop is designed to bring together computer scientists,
biologists and clinicians for exploring the current state-of-the-art
research taking place in all aspects of computational proteomics and
genomics, from basic science to clinical practice. The workshop intends to
provide a forum for the presentation of original research, valuable
software tools (basic algorithms, modelling, analysis, and visualization
tools, databases), and clinical fallouts, on topics of importance to
computational genomics and proteomics.


TOPICS OF INTEREST
The topics of interest will include but will be not limited to:

Data management and analysis in Computational Proteomics and Genomics
o Computational methods for microarray
o Computational methods for mass spectrometry
o Pre-processing and analysis of microarray data
o Pre-processing and analysis of mass-spectrometry data
o Florescence-based methods and related image processing techniques
o Peptide/protein identification
o Protein structure prediction
o Applications of Data Mining, Neural Networks, Soft Computing for proteomics
o Software environments for proteomics and genomics workflows
o Exploration and visualization of proteomic and genomics data
o Data models and integration for proteomics and genomics
o Querying and retrieval of proteomics and genomics data
o Knowledge management, text mining and ontologies for proteomics and
genomics
o System biology ( protein-protein interactions, signalling networks)
o Parallel and Grid-based methods for  proteomics and genomics
o Service Oriented approaches for Life Sciences applications
o Standards in proteomics and genomics

Applications of Genomics and Proteomics in Clinical Practice
o Biomarker discovery (identification of molecular targets for early
detection, prognosis and treatment of diseases)
o Technologies and data models for phenotype, genotype and proteotype data
o Integration and analysis of genomics, proteomic, and clinical data for
medical applications
o Application of proteomics methods in clinical practice
o Advanced Electronic Patient Records
o Data quality and provenance
o Medical Images


PAPER SUBMISSION AND PUBLICATION

We invite original previously unpublished contributions that are not
submitted concurrently to a journal or another conference.
Each paper must be prepared following the IEEE 2-column format and should
not exceed the length of 6 (six) letter-sized pages, submitted
electronically using the paper submission system prior to the submission
deadline.
CBMS 2010 submission web site is http://www.cbms2010.debii.curtin.edu.au
All submissions will be peer-reviewed by at least three reviewers. The
proceedings will be published by the IEEE Computer Society Press. At least
one of the authors of accepted papers is required to register and present
the work at the conference; otherwise their papers will be removed from
the digital library after the conference.
Please contact cannataro AT unicz DOT it for any question.


IMPORTANT DATES
Submission deadline for regular papers: 24 Jun 2010
Notification of acceptation: 2 Aug 2010
Final camera ready due: 2 Sep 2010
Author registration: 2 Sep 2010


TRACK CO-CHAIRS:
* Mario Cannataro  (University “Magna Græcia” of Catanzaro, Italy)
* Giovanni Cuda  (University “Magna Græcia” of Catanzaro, Italy)
* Marco Gaspari  (University “Magna Græcia” of Catanzaro, Italy)
* Pierangelo Veltri  (University “Magna Græcia” of Catanzaro, Italy)

PROGRAM COMMITTEE (PROVISIONAL)
* Tim Clark, Harvard Medical School - MassGeneral Institute for
Neurodegenerative Disease, USA
* Giuseppe Di Fatta, University of Reading, UK
* Cesare Furlanello, FBK - Fondazione Bruno Kessler, Italy
* Christine Froidevaux, LRI-Bioinformatics Group - University Paris XI,
Orsay, France
* Concettina Guerra, University of Padova, Italy
* Pietro Hiram Guzzi, University “Magna Græcia” of Catanzaro, Italy
* Hasan Jamil, Wayne State University, Michigan, USA
* Ela Hunt, ETHZ, Switzerland
* Maria Mirto, University of Salento, Italy
* Stephen Pennington, Conway Institute, University College Dublin, Ireland
* Simona Rombo, University of Calabria, Italy
* Dennis Shields, Conway Institute, University College Dublin, Ireland
* Roberto Tagliaferri, University of Salerno, Italy
* Jason Wong, University of New South Wales, Australia





****************************************
New book release
Handbook of Research on Computational Grid Technologies for Life Sciences,
Biomedicine, and Healthcare
ISBN: 978-1-60566-374-6; 1,050 pp; May 2009 Published under Medical
Information Science Reference an imprint of IGI Global
http://www.igi-global.com/reference/details.asp?id=34292
Edited by: Mario Cannataro, University Magna Graecia of Catanzaro, Italy
****************************************
Prof. Mario Cannataro,
Informatics and Biomedical Engineering,
University "Magna Græcia" of Catanzaro,
Viale Europa (Località Germaneto), 88100 CATANZARO, ITALY,
Tel: 0961-369 4100, Fax: 0961-369 4073/4090, Email: [log in to unmask],
Web: http://bioingegneria.unicz.it/~cannataro/
****************************************

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