BioVRPi is a GM Lab project that focuses on Pi platforms employment in bioinformatics, with particular regards on genomics. The project aims to develop and offer a low-cost, stable, and tested bioinformatic environment for students and researchers involved in genomics and transcriptomics fields.

GM Lab focuses on the study of complex traits and diseases, which are increasingly prevalent in modern populations. Using established approaches such as Genome Wide Association Studies (GWAS) alongside advanced methods including genotype imputation and polygenic risk score (PRS), GMLab aims to identify the genetic determinants underlying these conditions.

GM Lab aims to understand the epigenetic mechanism regulating gene activity and function in humans. Through the use of well-estabilished methylation analysis techniques, GM Lab is investigating gene methylation profiles correlated to genetic and epigenetic disorders and dysfunctions. 

GM Lab aims to develop a pipeline for integrating genomics big data to allow a better understanding of physiological phenomenons underlying diseases, with particular focus on genes roles, and to discover possible biological markers that can be targeted during precision-medicine therapeutic regimens.

GM Lab emplys long-read sequencing technologies to enable comprehensive genomic characterization. By leveraging Oxford Nanopore sequencing, the lab generates long, contiguous reads that facilitate the resolution of complex genomic regions, structural variants, and repetitive elements, supporting advanced genomic and transcriptomic analyses.

GM Lab is involved in the study of longitudinal bacterial isolates collected from  cystic fibrosis patients and sequenced with NGS platforms. The objective is to analyse the genomic evolution of bacteria and identify the adaptive mechanisms which contribute to the successful chronic colonisation of the airways of cystic fibrosis patients.

GM Lab conducts microbiome analyses to characterize microbial community composition and function across diverse biological contexts. By combining 16S rRNA gene metabarcoding with shotgun metagenomic sequencing, the lab profiles taxonomic diversity and explores the functional potential of microbial communities, enabling integrated insights into host–microbiome interactions and their relevance to health and disease.

NGS technology have been improved at the point of cellular resolution. GM Lab focuses on Single cell analysis in transcriptomics to investigate changes in gene expression, regulation of isoforms and cell typing  for human traits and diseases.

GM Lab is involved in the study of post-transcriptional gene regulation in health and disease. We investigate circRNA-miRNA-mRNA networks, using computational (RNAseq, genomic data analysis) and experimental (cell biology, transcriptomics and proteomics techniques) methods.