Topics in Computational Biology
This is a two-week course taught by Jotun Hein. It is aimed a researchers/students with a strong quantitative background (mathematics, physics, statistics, computer science,…) that wants an overview of computational biology with a wish to do research in the area. Each day is devoted to a topic. Examples of projects can be found at Projects. Beyond this the course should be self-contained. Lectures, Practicals, Exercises and Project Preparation each lasts 90 minutes.
Day 1: Molecular Evolution
Lecture: Models of Sequence Evolution
Chose Project and collect literature
Read miklos et al, study slides from day 2 and find questions.
Day 2: Statistical Alignment
9.00-10.30 Lecture: Statistical Alignment
11.00-1.00 Prepare Projects
2.00-4.00 Prepare and Exercise: Jukes-Cantor Model
Read Ponting, study slides from day 3 and find questions.
Day 3: Comparative Genomics
Lecture: Comparative Genomics
Practical: Models of Sequence Evolution
Read HSW chapt 1, study slides for day 4 and find questions.
Day 4: Gene Genealogies
Lecture: Population Genetics and Gene Genealogies
Prepare Exercise: Statistical Alignment
Read HSW chapt 5, study slides for day 5 and find questions.
Day 5: Inferring Recombination
Lecture: Inferring Recombination Histories
Rank mini projects
Practical: Statistical Alignment & Footprinting
IG paper, study slides from day 6 and find questions
Day 6: Integrative Genomics
Lecture: High throughput, Structure of Integrative Genomics and GF mappings
Read Ideker, study slides from day 7 and find questions.
Day 7: Networks
Present mini projects
Practical: Detecting Recombinations
Read Rune notes, study slides from day 8 and find questions.
Day 8: Grammars and Annotation
Lecture: Grammars and RNA/protein gene prediction
Study slides from day 9 and find questions.
Day 9: Analyses and Functional Explanation
Lecture: Analyses and Functional Explanation
Practical – Integrative Data Analysis – Mapping
Study project presentations of each other and find questions.
Day 10: Project Presentation/Discussion
Project 1 – Population Genomics: Selective Sweeps
Project 2 – Molecular Evolution: LUCA
Project 3 – Genomics : Somatic Cell Genealogies
Project 4 – Comparative Genomics: Genomic Dark Matter
Project 5 - Integrative Genomics: Metabonomics
The two-week course should give an overview of computational biology at present and outline problems suited for research projects