CALOGERO Raffaele Adolfo

Strutture di riferimento
Curriculum Vitae
Attività scientifica
My research experience was devoted to the development and optimization of analysis workflows and in mining transcription-based experiments, mainly in the oncology framework. An important aspect of my past and present work was the constant focus on new technologies (e.g. today single-cell and single-molecule sequencing) and their integration in our analysis workflows.
I started my journey in Bioinformatics in latest 90’s when I developed a tool to simulate, for windows-based PCs, a molecular biology laboratory (Iazzetti, et al., 1998). In 1998, I established at University of Torino the Genomics and Bioinformatics unit (B&Gu). B&Gu is an interdisciplinary group devoted to the study of multifactorial diseases by mean of high throughput technologies - i.e. microarray, Next Generation Sequencing – and bioinformatics. Since then my interests moved to research topics in which computational approaches could be used to mine biological data. Those years were the period in which expression microarrays started to be an effective tool to investigate genes involved in diseases and general biological processes. I was involved in various studies in which microarray data analysis played an important role. In collaboration with the group of cancer immunologists leaded by Prof. Forni at University of Torino, I focused the work of my group on the identification ofnew targets for anti-tumor vaccination protocols Because of my experience in microarray data analysis, my group was involved in a large number of collaborations in Italy and abroad. It is notable that, using gene expression microarrays, we were able to identify for the first time the presence of coding transcripts in circulating blood vesicles (Bruno,et al., 2009; Deregibus, et al., 2007; Herrera, et al., 2010), today a very hot topic in the field of biomarker discovery.
More recently we move our interest to single-cell transcriptomics both focusing in tool development (Alessandrì et al. Gigascience 2019) and data analysis (Rodriguez-Fraticelli et al. Nature 2018).