About Us

Scientific Director:

Prof. Paolo Provero (Department of Molecular Biotechnology and Health Sciences)

Steering Committee:

Prof. Raffaele Adolfo Calogero (Department of Molecular Biotechnology and Health Sciences)

Francesca Cordero, Ph.D (Department of Computer Science )

Prof. Mario Giacobini (Department of Veterinary Sciences)

Prof. Enzo Medico (Department of Oncology)

Core Staff

Ugo Ala, Ph.D.

Davide CorĂ , Ph.D.

Claudio Isella, Ph.D.

Our Mission

GenoBiToUS was started in September 2015 to help research laboratories in life sciences to take full advantage of -omics technologies. The cost of Next Generation Sequencing (NGS) is now low enough to be affordable by small research laboratories. However the data must be analyzed to extract useful information, and this still requires a specific set of statistical and computing skills beyond those of a typical life scientist.

GenoBiToUS supports life scientists in designing, conducting and interpreting NGS experiments and other genome-scale assays, and in exploiting public domain data to answer biological questions. We have many years of experience in bioinformatics and computational biology, both collaborating with experimental labs and developing our own research program.

In practice

Through our core staff and our network of collaborators we can provide bioinformatic support for several types of projects including:

  • Genomics
    • whole genome sequencing
    • exome sequencing
  • Transcriptomics
    • expression profiling
    • analysis of alternative splicing
    • fusion transcripts
    • microRNA expression profiling
  • Epigenomics
    • DNA methylation and histone modifications
    • transcription factor binding
  • Regulatory sequence analysis
    • motif analysis
    • prediction of transcription factor binding
    • prediction of microRNA targets
  • Functional genomics
    • coexpression networks
    • enrichment analysis (Gene Ontology, Human Phenotype Ontology, Reactome, etc.)
    • disease gene prediction and prioritization
    • eQTLs
  • Data mining
    • Gene Expression Omnibus
    • TCGA