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Bioinformatics

Bioinformatics

Code	11857
Year	2
Semester	S2
ECTS Credits	6
Workload	PL(30H)/T(30H)
Scientific area	Biotecnologia
Entry requirements	N/A
Mode of delivery	Face-to-face
Learning outcomes	The course aims to introduce students to different algorithms and computational techniques used in modern bioinformatics and to their application in solving problems in biology and medicine, with emphasis on applications of molecular biology. At the end of this course students should be able to: - Know how to parameterize adequately the most common search and sequence alignment algorithms. - Understand the motivations, assumptions and limitations of computational techniques that are applied to solve problems in biology. - Identify research directions in Bioinformatics.
Syllabus	>> Theory 1. Algorithms: getting started 2. Algorithms for sequence analysis 3. Algorithms for alignment of biological sequences. 4. Algorithms for multiple alignment of biological sequences. 5. Algorithms for motifs search 6. Data modelling >> Practice 1. Branching and Iteration 2. String Manipulation 3. Decomposition, Abstractions, Functions 4. Python & Rosalind 5. Python & Pandas
Main Bibliography	- Lecture notes “Introduction to Computer Science and Programming in Python”, Massachusetts Institute of Technology, 2021. - Lecture notes “Biology Meets Programming: Bioinformatics for Beginners”, University of California, 2021. - Bioinformatics with Python Cookbook, 2nd edition, Tiago Antão, Packt Publishing, 2018. - Bioinformatics: An Introduction, 3th edition, Jeremy Ramsden, Springer-Verlag London, 2015.
Language	Portuguese. Tutorial support is available in English.