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A.Y. 2019 / 2020

First semester
Type of Learning Activity 
Related/additional subjects
Study Path 
[PDS0-2018 - Ord. 2018] common
Mutuato: SM35 - 480SM - BIOINFORMATICS
Teaching language 


Learning objectives 

The course will provide students with basic knowledge of bioinformatics, genomics and molecular biology and will develop the following skills
D1. Knowledge and understanding. Understanding of bioinformatics issues and techniques used for genomic data analysis. Knowledge of public databases and international standards for the distribution of genomic data.
D2. Applied knowledge and understanding. Ability to develop, use and integrate different bioinformatics techniques and genomic databases for the solution of molecular problems.
D3. Autonomy of judgment. Ability to formulate a formal computational problem from an informal molecular problem.
D4. Communication skills. Ability to express oneself appropriately on bioinformatics and genomics topics.
D5. Ability to learn. Ability to consult and understand reference texts, scientific articles and international databases concerning bioinformatics applications and genomic data.


Basic notions of molecular biology, Unix programming and knowledge of a scripting language.


DNA/RNA/proteins. The Central Dogma of molecular biology. Notions of genomics. Bioinformatics databases and applications. Genome browsers and international standards for the distribution and exchange of genomic data. Next generation sequencing. Applications to analyze sequence data. Use of applications to analyze genomic data. Code development for the resolution of genomic problems. Evaluation of the developed code. Bioinformatics pipelines.

Teaching format 

Lectures and practical exercises in which the problems dealt with and/or emerged during the lessons are developed and resolved also making use of active learning methods.

Extended Programme 


End-of-course test 

Final practical test. Each student will have to solve a problem concerning the topics covered during the course by developing a code that performs a bioinformatic analysis.

Other information 



We will mainly refer to the following texts:

P. Compeau, P. Pevzner - Bioinformatics Algorithms, An Active Learning Approach 3rd Edition - Active Learning Publishers - ISBN-13: 9780990374633

V. Buffalo - Bioinformatics Data Skills, Reproducible and Robust Research with Open Source Tool - O’Reilly Media - ISBN-13: 978-1449367374

P. Pevzner, R. Shamir - Bioinformatics for Biologists - Cambridge University Press - ISBN-13: 978-1107648876

B. Alberts et al. - Molecular Biology of the Cell - Garland Science - ISBN-13: 978-0815344643

Other teaching material will be suggested by the teacher during the course.

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