Teaching

  • Advanced Genome Bioinformatics (AGB)  – Probabilistic modelling in Biology, Bayesian approach, prediction and classification, accuracy evaluation, feature selection, entropy and information theory, Markov models, hidden Markov models, HMM profiles, iterative methods, Gibbs sampling, Expectation-Maximization. The course aims to train future bioinformaticians to be able to start from the abstraction and mathematical formulation of biological problems, through the implementation of a working computer program and up to the critical evaluation of the data, including the accuracy analysis of the prediction tools.
  • Mathematics (MAT) - Linear Algebra, Vector Spaces, Matrices, Diagonalization, Singular Value Decomposition, Principal Component Analysis, Multidimensional Scaling, Optimization, Analytical Optimization, Approximate optimization, Support Vector Machines, Mixed Sample Decomposition. This course aims at training future bioinformaticians to be able to understand basic mathematical methods to transform and analyze data, and to learn how to implement working code to analyze actual data.

These courses are part of the Master in Bioinformatics for the Health Sciences of the Pompeu Fabra University.