BIOINFORMATICS
Stampa
Enrollment year
2020/2021
Academic year
2020/2021
Regulations
DM270
Academic discipline
ING-INF/06 (ELECTRONIC AND INFORMATION BIOENGINEERING)
Department
DEPARTMENT OF BIOLOGY AND BIOTECHNOLOGY "LAZZARO SPALLANZANI"
Course
Curriculum
PERCORSO COMUNE
Year of study
Period
2nd semester (01/03/2021 - 14/06/2021)
ECTS
6
Lesson hours
48 lesson hours
Language
English
Activity type
WRITTEN TEST
Teacher
SASSERA DAVIDE (titolare) - 4.5 ECTS
LESCAI FRANCESCO - 1.5 ECTS
Prerequisites
In order to be able to follow the course, the students must have a good grasp of the basic concepts of molecular biology. This should include understanding the concepts of gene, introns and exons, promoters, genome, transcription and translation and so on.
Learning outcomes
Aim of the course is to provide students with the basic knowledge of bioinformatic methodologies, tools and approaches that are essential to integrate molecular biology and genetics studies and researches nowadays.
While the students will not be proficient in bioinformatics after this course, the objective is for them to understand the broad range of applications that bioinformatics can have, and how helpful it can be for analysis of any biological dataset.
Course contents
The course is divided in four modules, each comprising theory explanation and praticals to apply them.
The first module is focused on:
Functions and goals of Bioinformatics.
NCBI and EBI sites.
Query tools for integrated databases. Biomedical primary and derivative databases.
Sequence comparison: basic notions and alignment tools. Multiple sequences alignment and evolutionary clustering. Genome Browsers. Regulatory elements in genome browsers. Transcriptional profiles in genome browsers and database. Analysis of nucleotide variations and repeated sequences. Human diseases and mutations. Bioinformatic analysis of alternative splicing. Bioinformatic analysis of microRNA targets.

The second module is focused on
Next-generation sequencing data analysis
Genome assembly and comparative genomics
Comparative transcriptomics

The third module is an introduction to the R language for bioinformatics

The fourth module is a series of seminars by an external teacher for a more in-depth analysis of one bioinformatic application, which this year is metagenomics
Teaching methods
All lessons will be held in a computer room. This will allow to constantly follow a theoretical explanation with a practical execution of the concept. The students will be asked to perform the tasks that the teacher explained, to maximize the connection between theory and practice. Based on the modules and the topics this will happen within the single lesson or in alternated lessons, thus one theoretical lesson followed by a practical one). The constant presence of tutors will allow to help students that are having issues during the practical parts.
Reccomended or required readings
Due to the quick changing nature of the discipline, the students should mostly lean on the slides and their own notes to study, however some reference textbooks are indicated below.
– Lesk A –Introduction to bioinformatics . Oxford Univ. Press, ed.

– Westhead DR, Parish JH, Twyman RM Bioinformatics (Instant notes)- Taylor and Francis, ed.

- NCBI Help Manual (http://www.ncbi.nlm.nih.gov/books/NBK3831/)
Assessment methods
The students will be tested through a single examination. The test will be divided in a written part and a practical part, to allow to evaluate the preparation of the students on the different course modules. The written part will include open and multiple answers questions. The practical part will ask the student to solve basic bioinformatic issues using databases and the R language.
Further information
The students will be tested through a single examination. The test will be divided in a written part and a practical part, to allow to evaluate the preparation of the students on the different course modules. The written part will include open and multiple answers questions. The practical part will ask the student to solve basic bioinformatic issues using databases and the R language.
Sustainable development goals - Agenda 2030