This course focuses on studying the technologies needed to transform and manipulate biological data. In particular it is focused on tools that allow the analysis of large sequencing data sets with the aim of obtaining reproducible and robust biological results. For this reason, 2 credits of the course are dedicated to the introduction of the linux environment and the tools included for the manipulation of data. The second half of the course (the remaining 2 credits) is dedicated to the fundamentals of programming illustrated using the python language and applications to sequence analysis.

ations to sequence analysis.

Linux:
- Setting up and management of a bioinformatics project in a linux environment
- Project directories and directory structures
- Why Linux in Bioinformatics? Modularity and
Linux philosophy
- The environment variables
- Working with flows and redirection
- Managing and interacting with processes
- Working with remote machines
- Recovery of bioinformatics data
- Data compression and use of compressed data
- When using unix pipelines
- Inspecting and manipulating data with linux tools
- An introduction to genomic ranges
- Working with sequence data
- Basic Bash scripts


Python:
- Python installation
- Arithmetic operators
- Types of data (numerical, booleans, sets, words, sequence)
- Variables, expressions, statements
- Control instructions (if, while, for, break, continue)
- Functions
- The biopython libraries

Educational material provided by the teacher.