Computer Science

General goals: The general objective of the course is to transfer to the students knowledge of the state of the art of computational biology following the advent of massive sequencing technologies for the production of genomic and proteomic data. These bases are then necessary to allow students to achieve the skills for a proper analysis of the problems of their area and the ability to design and implement a software suitable for solving the proposed problem. Therefore the course is aimed at shaping a professional figure who is able to intervene in the resolution and management of IT projects in the biomolecular field. Specific goals: The course aims at training experts in biomedical data analysis and software systems designers who possess the basic knowledge of molecular biology and the technologies used to deal with the management of the enormous flow of data generated in this sector. These professional figures must be able, starting from the experimental data production platform (the problems arising from the data produced with massive sequencing will be particularly detailed), to establish which are the algorithms of interest for the analysis of the project raw data. They will also have to acquire a critical sensitivity and openness to the ability to define the data analysis protocol taking into account the available computing resources and optimize the analysis accordingly. At the end of the course, students will also present the management, integration and interrogation of the enormous amounts of data produced by the analyzes in order to obtain biological end results, effective and usable, and the production of software systems for the bioinformatics community. Knowledge and understanding: The training objectives are realized through lectures, laboratory activities and exercises in which simulations of work projects, classroom development or discussion with direct participation of students on problems and analysis of case studies are provided. During the exercises the students will learn how to plan and develop • a bioinformatic analysis pipeline for processing raw data provided by Next Generation Sequencing platforms (NGS) • the automatization and optimization of the NGS analysis pipeline • a software system for managing and querying the data produced by the analysis • the docking and molecular dynamics simulations of biological macromolecules in High-Performance-Computing environment. Critical and judgmental skills: Course students will acquire the ability to process complex and / or fragmentary information (for example, they will have to handle partially annotated sequences, ie only some of them will be associated with a chromosomal interval of a sequenced organism, and often annotated standard) and must arrive at a modeling of the data conceived in an original and autonomous way, chosen coherently with the biological scope of its experimental project. Communication skills: Students will be able to communicate with researchers in the biomedical area, in a clear, logical and effective way, using the methodological tools acquired during the course and through their own terms of computational biology. The acquisition of these skills will be tested through an oral examination and some projects developed in the laboratory. Learning ability: Students must have acquired the critical, original and autonomous ability to relate to problems of the computational biology projects and to independently apply the knowledge acquired during the course in view of a possible continuation of studies at a higher level (specialist degree) or in the broader perspective of cultural and professional analysis in the case of employment in the biomedical / bioinformatics area.