| First cycle degree courses | Second cycle degree courses | Single cycle degree courses |
| School of Science | ||
| DATA SCIENCE | ||
Course unit
BIOINFORMATICS AND COMPUTATIONAL BIOLOGY
SCP7079317, A.A. 2019/20
Information concerning the students who enrolled in A.Y. 2019/20
BIOINFORMATICS AND COMPUTATIONAL BIOLOGY
SCP7079317, A.A. 2019/20
Information concerning the students who enrolled in A.Y. 2019/20
Information on the course unit
| Degree course |
Second cycle degree in DATA SCIENCE SC2377, Degree course structure A.Y. 2017/18, A.Y. 2019/20 |
 bring this page with you |
|---|---|---|
| Number of ECTS credits allocated | 6.0 | |
| Type of assessment | Mark | |
| Course unit English denomination | BIOINFORMATICS AND COMPUTATIONAL BIOLOGY | |
| Website of the academic structure | http://datascience.scienze.unipd.it/2019/laurea_magistrale | |
| Department of reference | Department of Mathematics | |
| Mandatory attendance | No | |
| Language of instruction | English | |
| Branch | PADOVA | |
| Single Course unit | The Course unit can be attended under the option Single Course unit attendance | |
| Optional Course unit | The Course unit can be chosen as Optional Course unit |
Lecturers
| Teacher in charge | SILVIO TOSATTO | BIO/10 |
|---|
Mutuating
| Course unit code | Course unit name | Teacher in charge | Degree course code |
|---|---|---|---|
| MEP5070877 | BIOINFORMATICS AND COMPUTATIONAL BIOLOGY | SILVIO TOSATTO | ME2193 |
ECTS: details
| Type | Scientific-Disciplinary Sector | Credits allocated | |
|---|---|---|---|
| Educational activities in elective or integrative disciplines | BIO/10 | Biochemistry | 6.0 |
Course unit organization
| Period | Second semester |
|---|---|
| Year | 1st Year |
| Teaching method | frontal |
| Type of hours | Credits | Teaching hours |
Hours of Individual study |
Shifts |
|---|---|---|---|---|
| Lecture | 6.0 | 48 | 102.0 | No turn |
| Start of activities | 02/03/2020 |
|---|---|
| End of activities | 12/06/2020 |
| Show course schedule | 2019/20 Reg.2017 course timetable |
| Prerequisites: | Basic knowledge of bioinformatics, e.g. alignment methods and databases. |
| Target skills and knowledge: | The course aims to comunicate bioinformatics methods for protein analysis. Moreover, it intends to allow the student to learn how to perform advanced computational research using available bioinformatics tools. |
| Examination methods: | The exam is composed of four parts, each of which has to be passed: (weight in parenthesis)
1) Practicals (25%) 2) Journal club presentation (25%) 3) Final essay on an unknown protein (25%) 4) Oral exam (25%) |
| Assessment criteria: | The following criteria are evaluated:
1) understanding of concepts and algorithms presented in class 2) ability to apply the concepts described in the lesson on real problems 3) critical capacity to be able to use the methods in the most appropriate, choosing from alternatives 4) display capacity and critical discussion during the journal club |
| Course unit contents: | 1) Evolutionary reletationship between protein structure / function / interactions
2) Folding and evolution theories of proteins 3) Prediction of 3D structure by homology and ab initio methods; The CASP experiment 4) Prediction of structural features 5) Prediction of protein function; The CAFA experiment 6) Interactions between proteins 7) Concepts of Network Biology 8) Genotype-phenotype correlation and proteins; The CAGI experiment. |
| Planned learning activities and teaching methods: | The course consists of lectures, practical computer exercises and journal clubs. The exercises are to be carried out according to the instructions provided and complemented by the study of a different bioinformatics problem for each group. The journal club is divided into presentations of articles of recent literature. |
| Additional notes about suggested reading: | The E-learning site will provide numerous course materials. These include the slides, podcasts, lecture notes and journal club bibliography. |
| Textbooks (and optional supplementary readings) |
|
- Lecturing
- Laboratory
- Problem based learning
- Case study
- Interactive lecturing
- Working in group
- Problem solving
- Flipped classroom
- Loading of files and pages (web pages, Moodle, ...)
