Bioinformatics Supervisor
Undergraduate Supervisor, Dept. of Computer Science and Technology, University of Cambridge, 2021
Led 2-3 person study groups in working through theoretical and practical applications of core bioinformatics topics, including dynamic programming, phylogeny (UPGMA, Neighbour Joining, Parsimony), clustering (hard/soft K-means, hierarchical, Markov), genome sequencing (Hamiltonian and De Bruijn graphs), genome alignment (suffix tries and the Burrows-Wheeler Transform), and Hidden Markov Models (Viterbi algorithm, Baum-Welch learning).
Course Description
This course focuses on algorithms used in Bioinformatics and System Biology. Most of the algorithms are general and can be applied in other fields on multidimensional and noisy data. All the necessary biological terms and concepts useful for the course and the examination will be given in the lectures. The most important software implementing the described algorithms will be demonstrated.
Learning objectives
At the end of this course students should
- understand Bioinformatics terminology;
- have mastered the most important algorithms in the field;
- be able to work with bioinformaticians and biologists;
- be able to find data and literature in repositories.