Iceland
Topics in Computational Biology
Iceland 2-6 June 2009
This is a one-week course taught by Jotun Hein and Rune Lyngsø. It is aimed at researchers/students with a strong quantitative background (mathematics, physics, statistics, computer science,…) who want an overview of computational biology with a wish to do research in the area. Each day is devoted to a topic.
The students will be doing projects in groups. All projects in the course will be Reading-Presentation-Discussion projects, where the students will have to read up upon a topic and present and discuss it. Examples of such topics could be Population Genomics: 1000 genomes, Integrative Genomics: Basic data types, Comparative Genomics: Signals, Comparative Biology: Networks, Integrative Data Analysis – Mapping, Metabolomics, Proteomics, Transcriptomics, Epigenomics, Genomic Dark Matter, LUCA – Last Universal Common Ancestor, Somatic Cell Genealogies, Comparing Protein Structures, Advanced Evolutionary Models of the Nucleotide Substitution Process, Algorithms for predicting DNA assembling into a given shape,… These can be done part time in a week or two.
On some occasions we do Analysis projects, where all students will analyze data sets from a series of angles: association mapping, genome annotation, regulatory signals, signatures of selection,… Typically it will focus on a gene of special interest due to recent publications and would typically relate to some disease. This type of project takes 2-3 days full work, ideally by 10+ students with interest in a special data set.
On other occasions we do Research Project discussions/criticism. The projects will describe an idea for possible research. This has to be elaborated upon. These projects needs 4-8 weeks of full time work.
It is recommended that the students read the following articles before the course starts:
Yang, Z. (2009) Computational Molecular Evolution Chapter 1 OUP
Hein, Schierup and Wiuf (2005) Gene Genealogies, Variation and Evolution Chapters 1 & 5.
Davies, Rafnar, Hellenthal and Hein (2009) Integrative Genomics and Functional Explanation
Lyngsø (2009) RNA Structure Prediction Notes
Beyond this the course should be self-contained. The project presentations are expected to last 40-90 minutes. Lectures, Practicals, Exercises and Project Preparation each lasts 90 minutes.
Tuesday June 2nd: Molecular Evolution
9.00-10.00 Lecture: Models of Sequence Evolution
10.00-10.30 Lecture: Phylogenies
10.30-12.00 Practical: Phylogenetics (PHYLIP)
2.00-3.30 Lecture (L): Grammatical Models [Reading material]
3.30-5.00 Student Activity: Prepare projects
Wednesday June 3rd: Sequence Comparison
9.00-9.45 Lecture: Optimisation Alignment [PowerPoint]
10.00-10.45 Lecture: Statistical Alignment
11.00-12.00 Exercise: Jukes-Cantor and Rate Matrix
2.00-3.30 Practical: DNA Sequence Analysis (PAML+PHASE)
3.30-5.00 Student Activity: Prepare projects
Thursday June 4th: Population Genetics
9.00-10.45 Lecture: Population Genetics, Genealogies & Recombination [PowerPoint]
11.00-12.00 Practical: Statistical Alignment & Footprinting
2.00-3.00 Exercise: Stochastic Grammars
3.00-5.00 Student Activity: Prepare projects
Friday June 5th: Integrative Genomics (IG)
9.00-10.45 Lecture: High Throughput Data, Structure of IG, and Mapping G to F [PowerPoint]
11.00-12.00 Exercise: Statistical Alignment
2.00-3.30 Practical: Detecting Recombinations
3.30-5.00 Student Activity: Prepare projects
Saturday June 6th: Project Discussion/Presentation
10.00-11.00 Project 1 – Proteomics [Project Description]
11.00-12.00 Project 2 – RNA genes and their evolution [Project Description]
12.00-13.00 Project 3 – Molecular Evolution and Annotation of Influenza [Project Description]
13.00-14.00 Project 4 – Inference of Pedigrees
This course will run the week before Systems Biology Short Course. The two courses cover different topics and could both be taken which would be beneficial
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