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MSc Bioinformatics

Data Analysis of Large-Scale Experiments in Molecular Biology

go to the 7BBYMDAL module webpage

Content

Aims

To extend students' understanding of the theory of data analysis of large-scale experiments in molecular biology, as well as provide students with an overview of the current major areas of research in this field.

Learning Outcomes

At the end of this module students should be able to:

Provisional Syllabus

Microarray technologies

Microarray data processing

Finding differential expression

Finding transcription factors binding sites

Introduction to Gene Networks Models

Large-scale Gene Networks

Large-scale Protein Networks

Exam to coursework ratio 70:30
Assessment 1 exam, 1 seminar presentation
Normally examined in June
Course Structure 20 hours lectures, 10 hours tutorials

taught in the second term
Lecturers Eric Blanc, Roli Roberts, Sophia Tsoka, Thomas Schlitt
Prerequisites none

Module Schedule

Week/Lecturer Lecture
2 hrs
Seminar/Tutorial
1 hr
Week 1
Eric Blanc
Microarray technologies
cDNA arrays, competitive hybridisation oligonucleotide arrays for gene expression, exon arrays, tiling arrays
tutorial
Week 2
Eric Blanc
Microarray data processing
data quality control
background correction and empirical models for RNA hybridisation normalisation methods local regression, variance stabilisation, etc.
tutorial
Week 3
Eric Blanc
Finding differential expression I standard hypothesis testing, linear models with fixed and/or random effects
bayesian analysis empirical bayesian models, conjugate priors approaches
Journal Club (assessed)
Week 4 11.02.09
Eric Blanc
Finding differential expression II Clustering & biological interpretation of results tutorial
Week 5
Thomas Schlitt
Introduction to Gene Networks Models
transcriptional regulation
regulatory regions
finding consensus binding sites
transfac
what is a network model?
why do network modelling?
dynamic models of small gene networks: boolean, difference, differential and hybrid modelstranscriptional regulation
tutorial
Week 6
Thomas Schlitt
Large-scale Gene Networks
power-law structure, small world behaviour
large-scale gene networks
transcription networks
ChIP-chip networks
tutorial
Week 7 03.03.09
Thomas Schlitt
Large-scale Protein Networks I
protein interaction networks
literature networks
tutorial
Week 8
Thomas Schlitt
Large-scale Protein Networks II
metabolic networks
in course assessment
mock exam handout
Week 9
Thomas Schlitt
Large-scale Protein Networks III
Predicting gene functions from networks
Assessing predictions using ROC curves
mock exam submission
Week 10 tba mock exam results

Reading list