cbms 2010 - 5th Special Track Computational Proteomics and Genomics: Data Management and Analysis

5th Special TrackrrComputational Proteomics and Genomics: rData Management and Analysisrrhttp://staff.icar.cnr.it/cannataro/cbms2010 rrCALL FOR PAPERSrrGenomics 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. rrCurrently 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. rrApplication 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.rrProteomics 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.rrSeveral 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. rrComputational 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. rrThe 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.rrThis 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. rrTOPICS OF INTEREST rrThe topics of interest will include but will be not limited to:rrData management and analysis in Computational Proteomics and Genomicsrro Computational methods for microarrayrro Computational methods for mass spectrometryrro Pre-processing and analysis of microarray datarro Pre-processing and analysis of mass-spectrometry datarro Florescence-based methods and related image processing techniques rro Peptide/protein identificationrro Protein structure predictionrro Applications of Data Mining, Neural Networks, Soft Computing for proteomicsrro Software environments for proteomics and genomics workflowsrro Exploration and visualization of proteomic and genomics datarro Data models and integration for proteomics and genomicsrro Querying and retrieval of proteomics and genomics datarro Knowledge management, text mining and ontologies for proteomics and genomicsrro System biology ( protein-protein interactions, signalling networks)rro Parallel and Grid-based methods for proteomics and genomicsrro Service Oriented approaches for Life Sciences applicationsrro Standards in proteomics and genomicsrrApplications of Genomics and Proteomics in Clinical Practicerro Biomarker discovery (identification of molecular targets for early detection, prognosis and treatment of diseases)rro Technologies and data models for phenotype, genotype and proteotype datarro Integration and analysis of genomics, proteomic, and clinical data for medical applicationsrro Application of proteomics methods in clinical practicerro Advanced Electronic Patient Records rro Data quality and provenancerro Medical ImagesrrPAPER SUBMISSION AND PUBLICATIONrrWe invite original previously unpublished contributions that are not submitted concurrently to a journal or another conference. rrEach 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.rrCBMS 2010 submission web site is http://www.cbms2010.debii.curtin.edu.au rrAll 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.rrPlease contact cannataro AT unicz DOT it for any question.rrIMPORTANT DATESrrSubmission deadline for regular papers: 17 Jun 2010rrNotification of acceptation: 2 Aug 2010rrFinal camera ready due: 2 Sep 2010 rrAuthor registration: 2 Sep 2010rrTRACK CO-CHAIRS: rrMario Cannataro (University “Magna Græcia” of Catanzaro, Italy) rGiovanni Cuda (University “Magna Græcia” of Catanzaro, Italy) rMarco Gaspari (University “Magna Græcia” of Catanzaro, Italy) rPierangelo Veltri (University “Magna Græcia” of Catanzaro, Italy) rrPROGRAM COMMITTEE (PROVISIONAL)rrTim Clark, Harvard Medical School - MassGeneral Institute for Neurodegenerative Disease, USA rGiuseppe Di Fatta, University of Reading, UK rCesare Furlanello, FBK - Fondazione Bruno Kessler, Italy rChristine Froidevaux, LRI-Bioinformatics Group - University Paris XI, Orsay, France rConcettina Guerra, University of Padova, Italy rPietro Hiram Guzzi, University “Magna Græcia” of Catanzaro, Italy rHasan Jamil, Wayne State University, Michigan, USA rEla Hunt, ETHZ, Switzerland rMaria Mirto, University of Salento, Italy rStephen Pennington, Conway Institute, University College Dublin, Ireland rSimona Rombo, University of Calabria, Italy rDennis Shields, Conway Institute, University College Dublin, Ireland rRoberto Tagliaferri, University of Salerno, Italy rJason Wong, University of New South Wales, Australia