The course is split into three parts, each covering a separate aspect of bioinformatics. First part focuses on basic structural bioinformatics topics including using algorithms to predict protein secondary and tertiary structures, protein-ligand docking, as well as modelling protein dynamics. Second part looks into RNA sequencing data analysis, mapping read data to the transcriptome or genome and carrying out differential expression analysis. The third part concerns population data analysis by introducing basic concepts of population genetics and how these affect the population structure. Finally, these concepts are applied in genome-wide association analysis.

Aims and objectives

1. You will be able to predict protein secondary and tertiary structures using algorithms.
2. You will be able to conduct molecular docking for proteins and other molecules.
3. You will learn the basic concept of force field for modelling molecular interactions.
4. You will be able to preprocess and analyse both genome and transcriptome sequencing data.
5. You will be able to calculate differential expression from sequencing data and interpret the result in terms of pathway enrichment.
6. You will be able to calculate the population structure from population sequencing data and take this into account in genome-wide association analyses.
   
   

Syllabus

1. Introduction to protein structure.
2. Predicting protein secondary structures.
3. Predicting protein tertiary structures.
4. Molecular docking and molecular dynamics.
5. Sequencing data and quality control
6. Transcriptome sequencing, mapping to genome.
7. Differential expression analysis
8. Pathway enrichment, biological interpretation of results
9. Basic principles of population genetics
10. Population structure
11. Selection and adaptation
12. Association analysis
13. Wrap up / practical examples.
    

Assessment