The Bioinformatic Unit, established 30 years ago, has a strong expertise in genome analysis, ranging from the assembly and scaffolding processes to genome annotation and annotation query systems.

In the last ten years, we specialized in NGS data analysis: reads alignment, variant calling, variant annotation and prioritization, transcriptome and miRNA analysis, ChipSeq.

A tool that facilitates the analysis of human variants from exome and genome sequencing.

A computational approach for gene prioritization, based on the integration of gene functional associations. In particular, it focuses on the identification of novel putative associations between genes and genetic disorders.

Developed with an innovative strategy to perform fast gapped and ungapped alignment onto a reference sequence. It supports several data formats and allows the user to modulate very finely the sensitivity of the alignments. The program is designed to handle huge amounts of short reads generated by ILLUMINA, SOLiD and Roche-454 technology.

An algorithm that efficiently aligns Bi-Seq reads obtained either from SOLiD or Illumina. An accompanying methylation-caller program creates a genomic view of methylated and unmethylated Cs on both DNA strands.

A platform that offers many services for primer design and quality check.

Online resources
Our group specializes in genome sequencing, and our latest releases are available at

genomes cribi
The Genomes portal gives access to genomic data we maintain

High Performance Computing facility

The computing facility hosts computing platforms to support the aalysis of the growing volume of data. We have a dedicated cluster for both computation analysis and data storage. A node with 2 Tb is used for assembly-related projects, while the blade system with 384 cores is intensively used for NGS data processing.

  • HP Blade System C7000, with 32 nodes with 12 cores each, and equipped with 24, 48 or 96 Gb of RAM memory (384 cores, 1.5 Tb RAM total).
  • HP DL980, with 64 cores (8 processors) and a total of 2 Tb of RAM.
  • 2x HP SL6500, with Tesla GPU (1792 GPU cores)
  • 2x Disk Array HP, accounting for a total of 160 Tb of disk space.

Schematic representation of the bioinformatics cluster