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Development of bioinformatics tools for the management and the analysis of genome-wide data


The research team is involved in the establishment of a center for bioinformatics analysis applied to different kind of genome-wide data. In 2010 was founded CABGen, a center for Genomic Bioinformatics analysis.


A high performance parallel computational system (HPC) is available in the lab.


The development of computational architecture and the implementation of bioinformatics tools is performed in collaboration with Institute of Applied Mathematics and Informatic Technologies Applicate (IMATI), CNR, Pavia.



Analysis of next-generation sequencing data


The arrival of next generation sequencing technologies (NGS) has improved the genomic contest and it has changed the way we think about scientific approaches in basic and clinical research. This technology allows for the accrual of qualitative and quantitative information about any type of nucleic acid with an incredible amount of data and a limited cost compared to traditional sequencing methods. For this reason, in recent years the NGS approaches are preferred. For example, in gene-expression studies, microarrays are now being replaced by seq-based methods, which can identify and quantify rare transcripts without prior knowledge of a particular gene and can provide information regarding alternative splicing events (Metzker, 2010). 

NGS technologies are useful for many applications. These include variant discovery by resequencing targeted regions of interest or whole genomes, cataloguing the transcriptomes of cells, tissues and organisms (RNA-seq), genome-wide profiling of epigenetic marks and chromatin structure (ChIP-seq, methyl-seq and DNase-seq), and species classification and/or gene discovery by metagenomics studies (Mardis, 2008). 


One of the most important feature of NGS technologies is the production of a big amount of data (Tbyte) which require bioinformatics tools. For this reason, it is necessary to use specific bioinformatics systems and tools in order to store, manage and analyze data with a relevant biological information. 



  • Metzker ML. Sequencing technologies- the next generation. Nat Rev Genet 2010; 11(1):31-46.
  • Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet 2008; 24(3):133-141.


At the moment, we are developing bioinformatics procedures in order to analyze mRNA-seq data in the contest of CNR-MIUR “Invecchiamento” project, and ChIP-seq data in the contest of CNR-MIUR Epigenomica (EpiGen) project. 




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