Topics in Computational Biology
This is a two-week course taught by Jotun Hein and colleagues. 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 on 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, Comparative Biology: Protein Structures, Advanced Evolutionary Models of the Nucleotide Substitution Process, Algorithms for predicting DNA assembling into a given shape,… More examples are available at our reading project page. 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. Examples of this kind of project can be found at our analysis project page. These take 2–3 days full work, ideally by 10+ students with an interest in a special data set. On other occasions we do Research Projects. The projects will describe an idea for possible research, that has to be elaborated upon. Examples of projects can be found at our main project page. These projects need 4–8 weeks of full time work.
Preparation of the project discussion will take 4-8 hours. Beyond this the course should be self-contained. The project presentation is expected to last 40-90 minutes. Lectures, Practicals, and Project Preparation each last 90 minutes, and Exercises 60 minutes.
Schedule
Week 1
Day 1: Molecular Evolution
- 9.00–10.30
- Lecture: Models of Sequence Evolution and Phylogenies
- 10.30–12.00
- Practical: Molecular Evolution (Phylogenies – PHYLIP+)
- 2.00–3.30
- Lecture: RNA & Stochastic Context Free Grammars
- 3.30–5.00
- Student Activity: Prepare projects
Day 2: Sequence Comparison
- 9.00–10.45
- Lecture: Optimisation and 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
Day 3: Comparative Genomics
- 9.00–10.45
- Lecture: Comparative Genomics
- 11.00–12.00
- Exercise: Hidden Markov Models
- 2.00–3.30
- Practical: Ensembl and UCSC Browser
- 3.30–5.00
- Student Activity: Prepare projects
Day 4: Population Genetics
- 9.00–10.45
- Lecture: Population Genetics, Genealogies & Recombination
- 11.00–12.00
- Exercise: Coalescent
- 2.00–3.30
- Practical: Association Mapping & Recombination
- 3.30–5.00
- Student Activity: Prepare projects
Day 5: Networks
- 9.00–10.45
- Lecture: Networks
- 11.00–12.00
- Exercise: Network Counting
- 2.00–3.30
- Practical: Network Inference
- 3.30–5.00
- Student Activity: Prepare projects
Week 2
Day 6: Comparative Biology
- 9.00–10.45
- Lecture: Comparative Biology
- 11.00–12.00
- Exercise: Network Evolution
- 2.00–3.30
- Practical: Comparing Networks and Structures
- 3.30–5.00
- Student Activity: Prepare projects
Day 7: Integrative Genomics (IG)
- 9.00–10.45
- Lecture: High Throughput Data, the structure of IG, G → F
- 11.00–12.00
- Exercise: Expression Data Modelling
- 2.00–3.30
- Practical: Proteomics Analysis
- 3.30–5.00
- Student Activity: Prepare projects
Day 8: Analyses and Functional Explanation
- 9.00–10.45
- Lecture: Analysis and Functional Explanation
- 11.00–12.00
- Exercise: Graphical Models
- 2.00–3.30
- Practical: Integrated Analysis
- 3.30–5.00
- Student Activity: Prepare projects
Day 9: Systems Biology
- 9.00–10.45
- Lecture: Systems Biology
- 11.00–12.00
- Exercise: Dynamic Modelling of Biological Systems
- 2.00–3.30
- Practical: ODE inference
- 3.30–5.00
- Student Activity: Prepare projects
Day 10: Project Presentation/Discussion
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