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Specific Objectives

Specific objectives addressed in the project

Below are briefly outlined some specific objectives and skills that will be addressed and developed under Bioinformatics project; a specific and detailed description will be given in the description of the modules that make up the various orders.

The project proposes itself the bases for the following matters:

Methods for the Study of Complex Biological Models

Study of mathematical and statistical models for the analysis and simulation of gene regulatory networks.
For the analysis of genotypes and the inference of haplotypes.
For the structural prediction, comparison and classification of proteins.
For the analysis of gene expression data from experiments with time-course microarray.
To generate virtual gene expression data with statistical and biological plausibility.
Development of models for the study of the folding-misfolding and aggregation of protein from sequence information.
Identification of determining chemical-physical correlation structure-dynamics-function of proteins.
Develop methods for shape-based modeling and analysis of macromolecular forms.
Analysis of emerging properties in rewritable systems (expressions/graphs) for the modelling/emulation of biological processes.
Study of models for the representation of the dynamics of cell populations and tumour growth and cytotoxic agents.
Study of cellular metabolism models.
Development of models for blood flow in arteries and the drug perfusion in the tissues.
Implementation of System Biology for the study of human cell model.
Analysis of gene expression data through innovative clustering algorithms in metric spaces.

Databases, Data Mining and Classification Methods

Developing Machine Learning techniques, Modelling and Growing Up for the analysis of gene expression data from microarray.
Studying clustering models, logic programming and feature selection for the detection of TAG SNP.
Designing and developing databases for management, integration and functional annotation data from sequencing projects, analysis of gene expression and other biological data.
Developing new similarities techniques and complementarity between molecules based on geometry, structure and semantics of the entities involved.
Developing techniques to improve the storage of information in a appropriate structured manner, so to allow them an efficient retrieval, and display in a flexible and suited way to the needs of the physician and researcher.
Develop taxonomic systems classification of bacterial strains on the basis of analysis of similarities.
Implement Machine Learning techniques developed on a workflow management system for the intelligent analysis of data.
Designing a system of Data Warehousing and Data Mining for analysis of medical heterogeneous data.
Studying the learning processes in living organisms, in order to develop artificial devices capable of adapting to a changing environment (growing up).

Methodologies for Bioinformatics based on HPC and Grid Computing

Developing algorithms and tools in the treatment of proteomic and molecular dynamics data based on the calculation on high performance and Grid computing.
Building a high-performance system for the screening of macromolecules within reviews of Docking based on the use of local protein surfaces descriptors.
Developing ability to recover heterogeneous information using databases distributed in Grid, in order to extract new knowledge to be used in pharmacotossicological and pharmacodynamics studies.
Analysis of specific types of computer codes for high-performance HPC for DNA's information modelling.
Developing Bioinformatics programs for high performance programmable cards.
Development of methods for docking and molecular dynamics for the search for new medicines based on HPC and GRID.