Content (Syllabus outline)
4 to 5 students with different backgrounds (Bachelor degree in computers sciences, mathematics or life sciences) form a group. Up to four lecturers provide students different challenges that cover one or several topics:
- Types of data and data collection during experimental work.
- Experimental data analysis.
- Visualization of experimental data.
- Biomedical databases.
- On-line tools and programs for database analysis.
- Databases of nucleic acid sequences and amino acid sequences.
- DNA patterns, looking for hidden messages in the genome.
- Graph algorithms, genome sequencing.
- Comparing short biological sequences, such as short sequences of DNA or proteins.
- Dynamic programming, searching for mutations.
- Phylogeny algorithms.
- Clustering and principal component analysis.
- Determination of physico-chemical properties of DNA/RNA molecules based on nucleic acid sequence.
- Secondary structure of RNA.
- Biologically inspired methods: genetic algorithms, differential evolution, swarm intelligence.
- Mechanism and constant of binding.