The focus of the Pinello laboratory is to use innovative computational approaches and cutting-edge experimental assays such as genome editing and single cell sequencing to systematically analyze sources of genetic and epigenetic variation and gene expression variability in human traits and diseases.
The lab uses machine learning, data mining and high performance computing technologies, for instance parallel computing and the new cloud oriented architectures, to solve computationally challenging and Big Data problems associated with next generation sequencing data analysis.
Our mission is to use computational strategies to further our understanding of disease etiology and to provide a foundation for the development of new drugs and more targeted treatments.
We develop computational approaches to investigate different epigenetic factors that regulate the chromatin structure and the gene expression integrating NGS for instance: ChIP-seq, RNA-seq, ATAC-seq and Bisulfite-seq.
Single Cell Analysis
We have experience analyzing data from recent single cell assays for gene expression, such as single cell RNA-seq and multiplexed qPCR.
We embraced the new revolution in functional genomics made possible by the novel genome editing approaches such as CRISPR/Cas9 and TALEN developing new tools to understand and visualize the outcome of these wet lab experiments.