Area of interest: healthcare biotech
Type of activity: intensive course
More info: firstname.lastname@example.org
The aim of the course is to provide the basic scientific and technical knowledge for the analysis of complex biomolecular data and in particular for the analysis of NGS data, in order to meet the needs of many associations and research laboratories. In fact, reading and analyzing data from new generation sequencers has gained fundamental importance in the research of rare diseases including neuromuscular disorders. Hence, the need to have specific bioinformatics skills to extract information from files obtained from NGS instrumentation and, appropriately applying open source procedures, transform them into nucleotide sequences ready to be processed and analyzed. The most common types of NGS data analysis and the tools required for interpretation of the obtained results will be dealt with. This is a practical course, with a clear computer setting, independent of the specific NGS instrument and independent of a specific pathology.
The course is aimed at graduates in disciplines related to the degree programs of Physical and Natural Mathematics Sciences, Medicine, Biotechnology, Pharmacy and Engineering, also with PhD. There is a small reserve for students.
The course is divided into two parts. The first part, initial 2 days, guides you to learning R language by putting the trainer in writing, interacting and using the libraries available in the major public repositories (CRAN and Bioconductor). The second part of the course, lasting 3 days, starting from the file obtained by the NGS sequencer, guides the trainer in all the procedures needed to process it, align it, and make it usable for further analysis. Lessons will be structured in a theorical part and in a practical part. R software and other open source software will be used, including the Galaxy web server for processing and analyzing NGS data on real data.
The course teacher is the prof. Giorgio Valentini associate professor of Computer Science at the Department of Computer Science at the University of Milan. The lecturer will be supported by other members of his research team and tutor specialists of neuromuscular and rare diseases. Giorgio Valentini conducts his research work at the Unacleto Lab of the University of Milan, and specializes in developing and applying computational methods for the analysis of complex bio-molecular systems using a data-driven approach Based on automatic learning techniques.
Organizer: CIDP Italia ONLUS