Bioinformatics
A.Y. 2021/2022
Learning objectives
- Provide the student with the fundamental knowledge for the analysis of complex biological and medical data with Machine Learning methods.
- Introduce the student to the state-of-the-art computational methodologies to extract biological and medical knowledge from even massive collections of data or observations, even in presence of uncertain information, and to create predictive models for fundamental bio-medical applications.
- Provide the fundamental methodological tools to undertake scientific research according to international standards in the area of Bioinformatics and Computational Biology.
- Introduce the student to the state-of-the-art computational methodologies to extract biological and medical knowledge from even massive collections of data or observations, even in presence of uncertain information, and to create predictive models for fundamental bio-medical applications.
- Provide the fundamental methodological tools to undertake scientific research according to international standards in the area of Bioinformatics and Computational Biology.
Expected learning outcomes
- Ability of applying the main Machine Learning methodologies for the analysis of bio-molecular data aimed at both knowledge extraction and the construction of predictive models in Molecular Biology and Personalized Medicine.
- Understanding of issues related to large-scale biological and medical data processing.
- Ability to apply and adapt Machine Learning models developed in different application areas in the context of Bioinformatics and Computational Biology
- Ability to think critically and to question design and implementation choices.
These abilities will be evaluated through the combination of a software project and an oral discussion on the topics of the course.
- Understanding of issues related to large-scale biological and medical data processing.
- Ability to apply and adapt Machine Learning models developed in different application areas in the context of Bioinformatics and Computational Biology
- Ability to think critically and to question design and implementation choices.
These abilities will be evaluated through the combination of a software project and an oral discussion on the topics of the course.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Professor(s)
Reception:
Appointments by e-mail
Dept. of Computer Science, via Celoria 18, room 3011