Bioinformatics

General teaching training objectives in terms of expected learning outcomes.

1. Knowledge and understanding: The course aims to give the knowledge and basic and advanced skills to the analysis of bioinformatics data.
   
2. Applying knowledge and understanding: the student will acquire knowledge about the models and algorithms for analyzing bioinformatics data.
   
3. Making judgments: Through concrete examples and case studies, the student will be able to independently develop solutions to specific problems related to bioinformatics data analysis.
   
4. Communication skills: the student will acquire the necessary communication skills and expressive appropriateness in the use of technical language in the general area of bioinformatics and computational biology.
   
5. Learning skills: The course aims to provide students with the necessary theoretical and practical methods to deal independently and solve new problems that may arise during a work activity. For this purpose, different topics will be covered in class by involving students in the search for possible solutions to real problems, using benchmarks available in the literature.
   

Lectures.

Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

Attendance in class is mandatory.

To better follow the lectures, slides will be shared by the teacher.

The slides do not constitute a means of study, but help in learning the concepts explained in class.

1. Introduction to bioinformatics
   
2. Basic biology (Basics of molecular biology and genomics, Basics on DNA sequencing, NGS, and major data formats)
   
3. Main programming languages for bioinformatics (R and Biopython)
   
4. Databases: structure, usage, tools for access, practical examples in R and Python
   
5. Algorithms for sequence alignment (Local, global, pairwise and multiple alignment)
   
6. Omics data analysis:
   
• Genomic data analysis and interpretation
• Transcriptomic data (NGS and Microarray)
• Chip-seq, ATAC-seq interaction data
• Introduction to Single-Cell Sequencing
7. Network analysis in bioinformatics: theory and practical examples in R and Python
   
8. Advanced tools for reproducible workflows and pipelines in bioinformatics (Docker and Snakemake)
   

We recommend the use of the text "Fondamenti di bioinformatica". Authors: Manuela Helmer Citterich, Fabrizio Ferrè, Giulio Pavesi, Graziano Pesole, Chiara Romualdi. Zanichelli Publisher (2018).

Other updated resources will be indicated by the lecturer in the slides used in class.

The final examination consists of a written test and an oral interview in which a project agreed upon between the teacher and the student will be discussed.

The written test and the oral interview will be graded in thirtieths, and the final grade will be obtained as a weighted average between the evaluation of the written test (weight: 25% of the final grade) and the evaluation of the oral test (weight: 75% of the final grade).

The written test consists of a theory question on course topics that the student must argue to show a broad understanding of the subject.

The minimum grade to pass the written test is 16/30. Those who do not pass the written test will not be allowed to take the oral test. The written test can be viewed with the teacher at any time.

The minimum grade to pass the final exam is 18/30.

The project must be completed within 1 month of passing the written test. The project can be arranged with the teacher at any time. In case of written grade rejection, the project grade will be kept for the entire academic year. In case of rejection of the final grade, the student will have to retake the entire test (written and project).

Unless otherwise announced, the written exam is held at 10:00 a.m.

Notes:

• The use of any hardware tools (calculators, tablets, smartphones, cell phones, BT headsets etc.), books or personal papers during the written exam is prohibited.
  
• To take the exams, it is mandatory to make reservations using the appropriate form on the Student portal.
  
• Late reservations via email are not allowed. If no reservation is made, the exam cannot be verbalized.
  
• Verification of learning may also be conducted electronically, should conditions require it.