Base Knowledge
Basic knowledge of programming in Python, mathematics, and biology.
Teaching Methodologies
Theoretical Lectures: The theoretical lectures will be used to present the fundamental concepts. They will be supported by audiovisual resources, presentations, and practical on-line examples.
Laboratory Classes: The laboratory classes are of a practical nature and aim to allow students to apply the theoretical concepts learned in the theoretical lectures. They consist of practical exercises in Python and on the application of computational tools that are available online.
Learning Results
In this course, students acquire knowledge in the field of Bioinformatics, becoming familiar with relevant problems in the area of biology that are solved through the application of different computational techniques.
The course presents the main tools available via web access, such as databases containing information on the genomes of various species and computational applications for manipulating the stored data.
An important component of the course is the focus on the application of optimization and data analysis algorithms to real problems in the field of Bioinformatics.
Program
1. Introduction to Bioinformatics
1.1. Objectives of bioinformatics
1.2. Relevance of bioinformatics
1.3. Examples of Problems
2. Bioinformatics on the Web
2.1. Online Databases: Accessing, Searching and Collecting Information
2.2. Online computer applications
3. Sequence Alignment
3.1. Similarity measures
3.2. Alignment Types
3.3. Pair vs. Multiple alignment
4. Phylogeny
4.1. Construction and analysis of phylogenetic trees
4.2. Maximum parsimony vs. maximum likelihood methods
4.3. Application of clustering algorithms to determine phylogenetic relationships
5. Structural Bioinformatics
5.1. Structural levels of proteins
5.2. Protein Folding
5.3. Tools for Visualization and Structural Analysis
5.4. Protein structure prediction
6. Intelligent Data Analysis for Bioinformatics
6.1. Application of supervised and unsupervised methods to problems from the bioinformatics area
Curricular Unit Teachers
Francisco José Baptista PereiraInternship(s)
NAO
Bibliography
Lesk, A. (2020). Introduction to Bioinformatics, (5th Edition), Oxford University Press.
Jones, N., Pevzner, P. (2004). An Introduction to Bioinformatics Algorithms. MIT Press.
Claverie, J. M., Notredame, C. (2007). Bioinformatics for Dummies, Wiley Publishing.