|Persona di riferimento||Chiara BISHOP|
|Indirizzo e-mail per firstname.lastname@example.org|
|Recapito telefonico per contatti||+39 02 26422600|
|Aggiungi l'evento al calendario||
Workshop NETTAB 2008 focused on "Bioinformatics Methods for Biomedical Complex System Applications"
Biomedical research laboratories are moving towards an environment, created through
the sharing of resources, in which heterogeneous and complex health related data, such as molecular
data (e.g. genomics, proteomics), cellular data (e.g. pathways), tissue data, population data (e.g.
genotyping, SNP, epidemiology), as well as data generated by large scale analysis (e.g. Simulation
data, Modelling, Systems Biology) must be taken into account.
The future of biomedical scientific research will be to use massive computing data crunching applications, data grids for distributed storage of large amounts of data and to develop new approaches to the study of the medical implications of the genome-enabled medical science. Microarray, NMR, mass spectrometry, protein chips, gel electrophoresis data, Yeast-Two-Hybrid, QTL mapping, gene silencing and knockout experiments are all examples of technologies that capture thousands of data points, often in single experiments.
The NETTAB2008 workshop will focus on all aspects needed to provide the framework for understanding multi-scale, complex biological systems, from the single bio-molecule to the cell, across a wide range of clinical information.
In particular, a special emphasis will be given to combine theory, experiments, informatics, and technologies for an integrative systems approach to biological research, which is becoming increasingly multidisciplinary, multidimensional, information driven.
The following list is not meant to be exclusive of any further topics as stated above.
Submitted contributions should address one or more of the following topics:
- Focus theme topics
- Software engineering for organic computing
- Bio-inspired computing
- Multi-agent systems and cellular automata
- Complex adaptive systems
- Self-organization in biological systems
- Qualitative and quantitative measurements
- Model-driven system development for system biology
- Software design methodology for adaptive systems
- Mathematical and experimental methods for studies of complex biological systems from intracellular level
- Analysis and modelling of pattern forming processes using modern statistical methods
- Neuronal communication networks
- Database Integration
- Combined dry- and wet-lab studies
- Molecular Databases / Data Warehouses
- Prediction and Integration of Metabolic and Regulatory Networks
- Genotype . phenotype linkage
- Protein-Protein Interactions
- Microarray modelling and analyses
- Integrative Approaches for Drug Design
- GRID based bioinformatics applications
- HPC application for complex system simulation and analysis
- Identification of Gene Regulatory Networks
- Computational Systems Biology
- Computational Proteomics
- Optimization of Workflow for Complex Bioinformatics analysis
- Integrative modelling and simulation frameworks