Bioinformatics Research
Research in the Bioinformatics Laboratory aims:
- to develop new methods for the computational analysis of biochemical and genetics data
- to apply computational tools to the study of problems of biomedical relevance
- to train researchers in the field of bioinformatics and computational biology
The list below summarizes the efforts of the various research groups.
Genomics and Diseases (GAD)
The GAD research group carries out a bioinformatics analysis of
DNA/RNA/protein functional elements, alterations of which lead to
diseases. Genetic variations (both acquired and inherited modifications
in sequences) and epigenetic variations (in methylation patterns)
affect the functional elements leading to aberrations in molecular
processes such as DNA replication and pre-mRNA processing. The goal of this group is to carry out research leading to development of
computational pipelines that decipher functional elements on disease
genes, and that delineate associations with disease-causing
genetic/epigenetic variations. It is envisaged that this work will lead to
development of novel RNA/protein based therapies. (More...) |
Protein Modelling and Design (PSMD)The research of the PSMD group is focused on better understanding of the molecular functions of proteins by means of computational modeling studies. (More...) |
DOCKING LAB (DockL)Development of new tools and strategies for drug design and discovery by integrating structural modeling, high performance computing, physical-chemical informations, biology and medicine. (More...) |
Quantitative Systems Biology (QSB)
The activities of the QSB group mainly concern high-dimensional data
analysis, model development, and scientific computing in various
biological contexts. A biological system can be broadly defined by a
group of independent but interconnected elements that function together
to form a unified whole. Thus, a requirement of systems biology is that
in order to specify systems, many measurements must be made (mRNAs and
microRNAs, proteins, small molecules, and other cellular components). As
the available experimental data address only a very sparse patchwork of
cellular processes, usually inferred under limited numbers of
experimental conditions, we pursue methodological steps such as the
integration of global data sets, the fusion of approaches to the same
data measurements and their different levels of errors, the design of
search strategies in data spaces through metrics targeted to extract,
evaluate, and validate relevant biological information. (More...) |
Simulation and Modelling (SAM)
The SAM group design and implement
mathematical algorithms for the analysis of biological processes. (More...) |
RAGNO group
The focus of the RAGNO group is on developing algorithms for gene network
inference by integrative analysis of gene expression and genotyping
data, as well as metabolic and protein interaction networks from
metabolomics and proteomics data, respectively. (More...) |