| Code |
17252
|
| Year |
1
|
| Semester |
S1
|
| ECTS Credits |
6
|
| Workload |
PL(30H)/T(30H)
|
| Scientific area |
Informatics
|
|
Entry requirements |
n/a
|
|
Learning outcomes |
1. Identify and describe algorithms and techniques used in Bioinformatics.
2. Explore databases of biological interest and extract relevant information from them.
3. Explore tools of interest for problem-solving in molecular biology and biomedicine.
4. Explore existing implementations of the most common algorithms for various computational problems and implement their parameterizations appropriately.
5. Identify current research directions.
|
|
Syllabus |
1. Introduction to Computer Science Applied to Biological Sciences
2. Bioinformatics Tools, Algorithms, and Libraries
3. Databases of Biological Interest
4. Sequence Analysis Methods (Pairwise Alignments)
5. Methods for Obtaining Multiple Sequence Alignments and Building Phylogenetic Trees
6. Gene Expression Analysis Methods (Clustering and Biclustering)
7. Biological Networks and Protein Interaction Analysis Methods
8. AlphaFold and Protein Structure Prediction
9. Biological Data Processing and Analysis
|
|
Main Bibliography |
1.Bioinformatics: An Introduction, Jeremy Ramsden, Third Edition, Springer-Verlag London 2015.
2.Algorithms in Bioinformatics: A Practical Introduction, Wing-Kin Sung, CRC Press 2010.
3.Essential Bioinformatics, Jin Xiong Cambridge, University Press, 2006.
4.An Introduction to Bioinformatics Algorithms, N.C, Jones & P. Pevzner, MIT Press, 2004
5.Introduction to Bioinformatics, 4th Edition, Arthur M. Lesk, Oxford University Press, 2014.
6. Articles and material made available by the professor.
|
|
Teaching Methodologies and Assessment Criteria |
The assessment of the teaching-learning period consists of completing 5 practical worksheets (FP, solved individually), completing a portfolio of bioinformatics resources and tools (Prf, individual), solving and submitting a challenge (D, individual), and completing a project on biological data processing and analysis (P, group).
Weightings:
- 5 Practical Worksheets (5 x 2 points = 10 points)
- 1 Portfolio of Resources and Tools (2 points)
- 1 Challenge (3 points)
- 1 Project (5 points)
Attendance Criteria:
- Minimum attendance of 70% in the course activities.
- Minimum grade of 6 points.
Approval Criteria:
- Meet the attendance criteria.
- The grade for each practical worksheet must be equal to or higher than 50% (1 point each).
- Final grade equal to or higher than 50% (10 points) - Final grade = FP1 + FP2 + FP3 + FP4 + FP5 + Prf + D + P
Exams
Same weighting as the teaching-learning assessment, in which the practical worksheets will be replaced by an exam.
|
|
Language |
Portuguese. Tutorial support is available in English.
|