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.

Week 1

Day 1: Molecular Evolution


Lecture: Models of Sequence Evolution

Practical: Phylogenies

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

Prepare Projects

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 Projects

Prepare Exercise: Statistical Alignment

Do Exercise

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

Week 2

Day 6: Integrative Genomics

Lecture: High throughput, Structure of Integrative Genomics and GF mappings

Do Exercise

Discuss mini-project

Read Ideker, study slides from day 7 and find questions.

Day 7: Networks

Lecture: 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

Prepare Projects

Prepare Exercise

Do Exercise

Study slides from day 9 and find questions.

Day 9: Analyses and Functional Explanation

Lecture:  Analyses and Functional Explanation

Prepare Projects

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