Aim of the course is to train students in various fields of Bioinformatics, with particular regard to the knowledge of state-of-the-art tools used to support biological research. In detail, training objectives are: 1) Basic knowledge in Informatics/Bioinformatics 2) Biological databases: inquiry and programmatic access 3) Alignment of nucleotide and amino acid sequences 4) In silico structural and functional characterization of genes and proteins 5) Bioinformatic analysis applied to Next-Generation-Sequencing data.
EXPECTED LEARNING OUTCOMES:
KNOWLEDGE AND UNDERSTANDING. At the end of the course the students will get the following: the basic principles of bioinformatics, how biological databases are designed, managed, and queried, how sequences similarity search are performed, how to perform in silico characterization of genes and proteins and of how to analyse data from Next-Generation-Sequencing platforms. APPLYING KNOWLEDGE AND UNDERSTANDING. Understanding the computational approaches discussed in the lessons and their applications to specific problems. MAKING JUDGEMENTS. Be able to critically interpret the results obtained through the bioinformatics tools discussed during the course, as well as choose the ones most suitable to achieve a specific goal. COMMUNICATION SKILLS. Students should acquire the ability to transfer the acquired knowledge in a clear and comprehensible manner, even to people who are not in the field, and must demonstrate the ability to present the acquired information. LEARNING SKILLS. Be able to describe the topics of Bioinformatics in oral form. This ability will be developed by the active involvement of the students through class discussions and practical activities organized in the Informatics room on specific topics.
Basic concepts of computer science. Essential concepts on genomes. Primary and secondary databases. Sequence alignment algorithms. Phylogenetic trees. Next Generetion Sequencing platforms. Reconstruction and annotation of genomes. The big genomic projects. Transcriptome analysis. Proteins and proteomes. Bioinformatic methods for the analysis of protein sequences. Structural bioinformatics. Protein interactions. Big data projects. Scientific competitions.