The advent of next generation sequencing techniques (NGSTs) prompted the large-scale investigation of the relationship between diseases and variations discovered in the individual genomic sequences. The availability of high-throughput and low-cost re-sequencing techniques makes it possible to adopt genetic markers in prevention, diagnosis, prognosis, and therapy design. Recent studies have shown the big potential of deep sequencing techniques in addressing the clinical care in a personalized perspective. NGSTs allow detecting the genomic variations, including somatic mutations, single nucleotide polymorphism (SNP), insertion and deletions (indel), translocations and copy number variations (CNV). By this quantitative information on the transcript content of a cell and on allele-specific expression is obtained. Data on transcriptomics and exomics become crucial for understanding when variations promote peculiar alternative splicing patterns or gene up-/down-regulation. Two main factors hamper the complete exploitation of re-sequencing data in fundamental biomedical research and prevent its application in translational medicine: i) the difficulty of retrieving all the information on variations available in different data repositories; ii) the need of interpreting the variation data in the context of the complexity of the biological processes occurring at the cell level. In order to take advantage of the sequencing data is then necessary to develop computational tools suited to facilitating the annotation and the functional characterization of variations in the human genomes with the goal of understanding human genetic variations and assessing its role in the insurgence and development of diseases. This edition of the Bologna Winter School will focus on the state of art methods for data analysis of NGSTs and tools for deciphering information from deep sequencing data down to proteins, protein-protein interaction and the effect of mutations on protein stability.