Bioinformatics for molecular biology 2010

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Bioinformatics for molecular biology - Fall 2010


The aim of the course is to introduce students to bioinformatics resources and tools for molecular biology research by having some of the best researchers in Norway to talk about their field in general and then present their own work. Students are encouraged to bring a lap-top; we will be set up for in-course demonstrations as well as practical lab exercises. The course is intended for biology students or computer science/math students. No prior background in bioinformatics or computer science is required.

The course is jointly delivered by the Biotechnology Centre of Oslo, the Department of Molecular Biosciences (IMBV), the Department of Informatics (IFI) and the Norwegian University of Life Sciences. This course is one of the Ph.D. School courses offered by the Biotechnology Centre of Oslo ( The UiO page for this course is

Registration will be open in May of 2010. Check back here for details

MBV-INF 4410 (M.Sc. level course code)10.0 study points

MBV-INF 9410 (Ph.D. level course code) 10.0 study points

MBV-INF 9410A (Ph.D. level course code) 8.0 study points

The course consists of two weeks of lectures, a final take-home exam (one week) and an essay (10 to 20 pages) to be completed by end of October.

Ph.D. level students may opt to take the course without the essay for only 8 study points.

Please bookmark this page. All future changes or announcements for the 2010 course will be posted to this page.

        (about course administration) 
        (about course content)

Dates and times

The course will occur September 6th to 17th.

Each day will consist of three time slots for lectures and/or practical labs between 9 AM and 4 PM.



Directions to Forskningsparken can be found at

Mondays to Friday morning: Room 10 (one level down from the main entrance) The room is booked each day from 09:00 to 16:00 EXCEPT Fridays when the room must be vacated from 12 to 13:30.

Exceptions: none so far

Lunch is on your own between 1:00 PM and 2:15 PM. Please completely vacate the room during these lunch times.


Please note:
The schedule displayed below is based on last years course 
Ongoing changes will be made to this page as we organize 
speakers before and during the course.  
Requests and suggestions are welcome.
Bioinformatics 2010
Time Speaker Contact Details and suggested readings
Day 1 - Monday September 6
9.00-9.15 Ian Donaldson Introduction
9.15-11.00 Ian Donaldson

Exploratory data analysis Extra material

11:15-13.00 Bjørn-Helge Mevik

Introduction to R - Presentation


Bjørn-Helge Mevik

Katerina Michalickova

Introduction to R - Lab

Day 2 - Tuesday September 7
9.15-11.00 Clara-Cecilie Günther

An introduction to statistical inference

11:15-13.00 Einar A. Rødland

Multiple hypothesis testing

14.15-16.00 Ian Donaldson

MySQL installation and tutorial

Day 3 -Wednesday September 8
9.15-11.00 Leonardo Meza-Zepeda Dept. of Tumor Biology, Rikshospitalet-Radiumhospitalet Medical Center

Microarray technology

Integrated genomic analysis

11:15-13.00 Ståle Nygård

Microarray data analysis

14.15-16.00 Ståle Nygård R Microarray data analysis lab
Day 4 - Thursday September 9
9.15-11.00 Torbjørn Rognes

Searching sequence databases and multiple sequence alighments.

11:15-13.00 Geir K. Sandve Motif scanning and discovery in DNA

Geir K. Sandve


Vegard Nygaard

Sequence lab



General TF analysis - a simple approach

Day 5 - Friday September 10

Sveinung Gundersen

Geir K. Sandve

The Genomic Hyperbrowser

The Hyperbrowser tutorial

Hyperbrowser tutorial

11.15-12:00 Dave W. Ussery Comparative genomics

Cautionary Tales for Next Generation Sequencing

12.00-13:30 Lunch -vacate room
13:30-14:15 Dave W. Ussery Comparative genomics

Comparative genomics - bacterial genomes.

14.15-15.30 Sequence lab

Three views

EColi. Atlas


GeneWiz Browser

Physical Maps of Chromosomes

The 1000th Genome

16.00- TGIF Forskningsparken pub
Day 6 - Monday September 13
9:00-11:00 Robert Lyle

High throughput sequencing

11:15-13.00 George Magklaras

Biological sequence mining with MRS

MRS and EMBOSS lab

13:00-14:00 Lunch
14.15-16.00 Kamran Shalchian-Tabrizi (TBC)


Day 7 - Tuesday September 14
9.15-11.00 Jon K. Laerdahl

Structural biology review


Installing PyMol

11:15-13.00 Jon K. Laerdahl

Structural bioinformatics tools, predictors, and 3D modeling

14.15-16.00 Jon K. Laerdahl PyMOL and structural biology tutorial
Day 8 - Wednesday September 15
9.15-11.00 Jon K. Laerdahl Structural modeling tutorial: Practical exercises

Modeling Guide

11:15-13.00 Jon K. Laerdahl Modeling excercises
14.15-16.00 Jon K. Laerdahl Homology modeling exercise
Day 9 - Thursday September 16
9.15-11.00 Ian Donaldson

Interaction data resources

Identifier conversion excercise

11:15-13.00 Sabry Razick, Paul Boddie

Cytoscape tutorial and lab

14.15-16.00 Sabry Razick, Paul Boddie iRefScape plugin tutorial and lab. See and Tutorial :
Day 10 - Friday September 17
9.15-10.00 Ian Donaldson GO DAVID and IRefScape revisited

Working with gene lists and over-representation analysis

10.15-11.00 Arne Gjuvsland

Causally cohesive genotype-phenotype modelling - systems biology meets genetics

11.15-12.00 Jon Olav Vik

cGP map of the cardiomyocyte

12.00-13:30 Lunch -vacate room
13:30-14:15 Katerina Michalickova

TITAN cluster for beginners

Written assignment

Students enrolled in MBV-INF4410 or 9410 must complete a written assignment as part of the course requirements.

The assignment is due by Friday, October 29th. It should be emailed to ian.donaldson at preferably as a PDF document (Microsoft Word or OpenOffice is also acceptable). The assignment is to be between 10 pages and 20 pages (2000 to 4000 words). This is a rough guide (I wont be counting pages and words - quality and conciseness count more than quantity).

Topics include:

1) write an explanation of three or more methods that were covered in the course. These should be simple explanations aimed at someone approaching the topic for the first time. Your explanation may include derivations of equations (if they are clearly explained), figures or tables. Use examples. Describe how the concept can be applied to a problem in biological research and what limitations the method has. List any resources you use as well as references to additional material that a student might use if they want to follow up on the topic further. Please indicate whether your material may be used on the course's wiki page.

2) describe how you would use two or more of the methods covered in the course in your own research. Your proposal may include figures or tables. Give a short introduction to your problem area, clearly state your hypothesis and how you think it might be addressed by each of the methods. Provide justifications for your proposal as well as expected outcome. Describe potential risks (say, the method provides no meaningful results) and what you would do to mitigate this risk. List any resources you use.

3) you may define your own alternative topic. Please send an email to ian.donaldson at to have your topic approved first.


Please note:

The exam for this course will be a one week take home exam.  

The exam will be emailed to candidates on Monday, September 20th before 5PM.  

The exam must be emailed back by Monday, September 27th at 5 PM to 

Torill Rortveit ( as a single PDF document

(Microsoft Word or an Open Office Document is also acceptable).  The document 

should be named with your candidate number only (e.g. 1.pdf).  Do not place your 

name in the document.


Bioinformatics links relevant to the course

Bioinformatics Links 2010
Name URL Description
Day 1-2: Statistics
StatSoft textbook Good overview of methods and concepts
SAS manuals Thorough overview of analysis procedures found in SAS
GraphPad See the GraphPad statistical guide for easy introductions to many concepts in statistics
R The Comprehensive R Archive Network

Introduction to R

Exploratory data analysis

Hypothesis testing See the CBW course on "Exploratory Data Analysis Essential Statistics using R" at the bottom of this page. Slides and lecture recordings from Modules 1-3 cover much of the same material covered in the first two days of this course.
Learning R A Quick Guide to Teaching R Programming to Computational Biology Students
R reference card A reference card for R syntax
UCLA tutorials Useful example code while learning R
R vs. other languages A brief description of how R differs from other programming languages. Useful if you already know a programming language.
Which test do I use An interactive guide to choosing which statistical test to use.
EMBNet Microarray course An online course with R/Bioconductor example tutorials
EMBNet tutorials Other helpful tutorials with R examples related to biostatistics
SIB tutorials Portal to the SIB bioinformatics tutorials - includes R, Unix, Perl, statisitics and lots more.
CBW tutorials Portal to the Canadian Bioinformatics Workshop material. Includes R, statistics and lots more.
Day 3 - Microarrays
NMC Norwegian Microarray Consrtium
MACF UiO MicroArray Facility
Bioinformatics core facility The Bioinformatics Core Facility established at Rikshospitalet-Radiumhospitalet (RR) will provide its users at RR and the University of Oslo with a range of services within bioinformatics, including analysis of DNA and protein sequences, analysis of microarray data, protein structure analysis and access to useful databases and web services
Day 4 - 5 Sequence
RSAT RSAT A collection of several motif-related tools
ConTra ConTra A more user-friendly tool for matching a collection of Position Weighted Matrices against promoter sequences across species
Day 6 -
Day 7 -
Required files [Sample network[1]] [Node atributes[2]] Please download these and uncompress before using
Cytoscape Cytoscape home page
Cytoscape Tutorial on Cytoscape
Cytoscape Solution to common problem with working with large networks in Cytoscape.
iRefIndex Cytoscape plugin iRefIndex installation
iRefIndex iRefIndex wiki
iRefIndex publication Full details of iRefIndex
DAVID Nature Protocols paper
GSEA Gene Set Enrichment Analysis application

Bioinformatics Mailing Lists

If you are interested in being informed of future courses, talks and new related to bioinformatics in the Oslo region, then consider signing up for the cbo mailing list.

You might also consider the Norwegian-wide bioinformatics email list. You can sign up at

Both lists are run by members of the Norwegian Bioinformatics Platform.