IEEE CBMS-2008 Special Track on Computational Proteomics - Deadline approaching
21st IEEE International Symposium on COMPUTER-BASED MEDICAL SYSTEMS
June 17-19 2008 Jyväskylä, Finland.
Special Track
Computational Proteomics: Management and Analysis of Proteomics Data
New submission deadline (extended): February 4, 2008
http://bioinformatics.unicz.it/cbms2008/
cannataro [at] unicz [dot] it
CALL FOR PAPERS
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 Special Track 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, from basic science to
clinical practice. The Special Track 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
o Computational methods for microarray
o Computational methods for mass spectrometry
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 workflows
o Exploration and visualization of proteomic data
o Data models and integration for proteomics
o Querying and retrieval of proteomics data
o Knowledge management, text mining and ontologies for proteomics
o System biology ( protein-protein interactions, signalling networks)
o Parallel and Grid-based methods for proteomics
o Service Oriented approaches for Life Sciences applications
o Standards in proteomics
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. Unlike workshops, where position papers and reports on initial and intended work are appropriate, papers
selected for a Special Track should report on significant unpublished work suitable for publication as a conference
paper.
Each contribution must be prepared following the IEEE 2-column format and should not exceed the length of 6 (six)
Letter-size pages and submitted electronically before the paper submission deadline. All submissions including
special track papers will be done electronically via the CBMS web submission system, which will be open
approximately one month before the deadline. Prospective authors should choose the ST2: Computational
Proteomics: Management and Analysis of Proteomics Data Special Track title when submitting a paper.
All submissions will be peer-reviewed by at least three reviewers of the Special Track Program Committee. All
accepted papers will be included in the conference proceedings published by IEEE CS Press. At least one author must
pay the registration fee before March 28, 2008 for each accepted paper.
Please consult http://cbms2008.it.jyu.fi or http://bioinformatics.unicz.it/cbms2008 for further information.
IMPORTANT DATES
Paper submission due (extended): February 4, 2008.
Notification of acceptance for papers: February 28, 2008.
Final camera-ready paper due: March 28, 2008.
Pre-registration Deadline: March 28, 2008
CBMS 2008 Symposium days: June 17-19, 2008.
TRACK ORGANIZERS:
* 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
* Hasan Jamil, Wayne State University, Michigan, USA
* 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
* Domenico Talia, University of Calabria, Italy
* Jason Wong, University of Oxford, UK
June 17-19 2008 Jyväskylä, Finland.
Special Track
Computational Proteomics: Management and Analysis of Proteomics Data
New submission deadline (extended): February 4, 2008
http://bioinformatics.unicz.it/cbms2008/
cannataro [at] unicz [dot] it
CALL FOR PAPERS
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 Special Track 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, from basic science to
clinical practice. The Special Track 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
o Computational methods for microarray
o Computational methods for mass spectrometry
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 workflows
o Exploration and visualization of proteomic data
o Data models and integration for proteomics
o Querying and retrieval of proteomics data
o Knowledge management, text mining and ontologies for proteomics
o System biology ( protein-protein interactions, signalling networks)
o Parallel and Grid-based methods for proteomics
o Service Oriented approaches for Life Sciences applications
o Standards in proteomics
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. Unlike workshops, where position papers and reports on initial and intended work are appropriate, papers
selected for a Special Track should report on significant unpublished work suitable for publication as a conference
paper.
Each contribution must be prepared following the IEEE 2-column format and should not exceed the length of 6 (six)
Letter-size pages and submitted electronically before the paper submission deadline. All submissions including
special track papers will be done electronically via the CBMS web submission system, which will be open
approximately one month before the deadline. Prospective authors should choose the ST2: Computational
Proteomics: Management and Analysis of Proteomics Data Special Track title when submitting a paper.
All submissions will be peer-reviewed by at least three reviewers of the Special Track Program Committee. All
accepted papers will be included in the conference proceedings published by IEEE CS Press. At least one author must
pay the registration fee before March 28, 2008 for each accepted paper.
Please consult http://cbms2008.it.jyu.fi or http://bioinformatics.unicz.it/cbms2008 for further information.
IMPORTANT DATES
Paper submission due (extended): February 4, 2008.
Notification of acceptance for papers: February 28, 2008.
Final camera-ready paper due: March 28, 2008.
Pre-registration Deadline: March 28, 2008
CBMS 2008 Symposium days: June 17-19, 2008.
TRACK ORGANIZERS:
* 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
* Hasan Jamil, Wayne State University, Michigan, USA
* 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
* Domenico Talia, University of Calabria, Italy
* Jason Wong, University of Oxford, UK
