Difference between revisions of "Bioinformatics course"

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||[http://donaldson.uio.no/wikifiles//images/2/29/Exploratory_data_analysis.pdf Exploratory data analysis] [http://bioinformatics.uio.no/wiki/Image:Exploratory_data_analysis_extra_materials.zip Extra material]
 
||[http://donaldson.uio.no/wikifiles//images/2/29/Exploratory_data_analysis.pdf Exploratory data analysis] [http://bioinformatics.uio.no/wiki/Image:Exploratory_data_analysis_extra_materials.zip Extra material]
 
||An introduction to statistical inference
 
||An introduction to statistical inference
||Multiple hypothesis testing
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||[[Media:Multiple_hypothesis_testing.pdf | Multiple hypothesis testing]]
 
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| ||Anja Bråthern Kristoffersen||TBA||Clara-Cecilie Günter
 
| ||Anja Bråthern Kristoffersen||TBA||Clara-Cecilie Günter

Revision as of 12:44, 24 November 2011

Bioinfo course logo.jpg
About this image

Bioinformatics for molecular biology - Fall 2011

November 21st to December 2nd

Description

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 (http://www.biotek.uio.no/ny-web/events/). The UiO page for this course is http://www.uio.no/studier/emner/matnat/molbio/MBV-INF4410/.

Registration is open now (June of 2011).

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 the middle of December.

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 2011 course will be posted to this page.

            Information: 
                 ragni.indahl@biotek.uio.no (about course administration) 
                 ian.donaldson@biotek.uio.no (about course content)
            Registration: 
                 torill.rortveit@imbv.uio.no

Dates and times

The course will occur November 21st to December 2nd.

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

New Place!

Mondays and Tuesdays:

Prolog Seminar room, Ole Johan Dahls Hus, IFI2

Gaustadalleen 23c

Same floor as entrance level. Use entrance nearest to Problemveien.

Wednesdays, Thursdays and Fridays:

Seminar room 510 in Veglaboratoriet Gaustadalleen 25

Fifth floor.


Map

This mapshows closest entrances to use for both buildings.

Closest T-bane

Forskningsparken.

Contacts during the course

Ian Donaldson (course coordinator) ian.donaldson@biotek.uio.no +47 99115149

Problems with room access or audiovisual

Sigrun Lien: 22852953

Line Valbø: 22852415

Programme

Note: The schedule displayed below is tentative. Ongoing changes will be made to this page as we organize speakers before and during the course. Requests and suggestions are welcome. For examples of material presented last year, see Bioinformatics for molecular biology 2010).

Week 1: Monday, November 21st - Friday, November 25th
Session 1 Session 2 Session 3
09:00 – 10:45 11:00 – 12:45 14:00 – 15:45
Mon. 21st Database lecture notes

Working with identifiers

Excercise

Install Perl
Ian Donaldson Ian Donaldson, Antonio Mora, Paul Boddie Ian Donaldson, Antonio Mora, Paul Boddie
Tue. 22nd Perl More Perl Perl lab
Antonio Mora Antonio Mora Antonio Mora, Paul Boddie
Wed. 23rd Introduction to R R lab R lab
Bjørn-Helge Mevik Bjørn-Helge Mevik, Katerina Michalickova, Antonio Mora Bjørn-Helge Mevik, Katerina Michalickova, Antonio Mora
Thur. 24th Exploratory data analysis Extra material An introduction to statistical inference Multiple hypothesis testing
Anja Bråthern Kristoffersen TBA Clara-Cecilie Günter
Fri. 25th Microarray data analysis Microarray data lab Gene Ontology Over-representation analysis in DAVID. Lab.
Ståle Nygård Ståle Nygård Donaldson
Week 2: Monday, November 28th - Friday, December 2nd.
Session 1 Session 2 Session 3
09:00 – 10:45 11:00 – 12:45 14:00 – 15:45
Mon 28th Interaction and pathway data Cytoscape lab Cytoscape plugin lab
Donaldson Donaldson Mora Boddie Donaldson Mora Boddie
Tue. 29th ht sequencing ht sequence lab
Robert Lyle Robert Lyle
Wed 30th Searching sequence databases and multiple sequence alignments Motif scanning and discovery in DNA Sequence lab
Torbjørn Rognes Geir Sandve Geir Sandve
Thur 1st Structural biology review, PyMOL and installing PyMOL Structural biology tools, predictors and 3D modelling PyMOL and structural biology tutorial
Jon K. Laerdahl Jon K. Laerdahl Jon K. Laerdahl
Fri 2nd Modeling guide Modeling excercises Homology modeling excercise
Jon K. Laerdahl Jon K. Laerdahl Jon K. Laerdahl

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, December 16th. It should be emailed to ian.donaldson at biotek.uio.no 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 biotek.uio.no to have your topic approved first.

Exam

Please note:

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

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

The exam must be emailed back by Monday, December 12th at 5 PM to 

Torill Rortveit (torill.rortveit@imbv.uio.no) as a single PDF document

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

should be named with the course code and your candidate number only 

(e.g. MBV-INF 4410-1.pdf).  Do not place your name in the document.
 

Bioinformatics links relevant to the course

Bioinformatics Links 2011
Name URL Description
Statistics
StatSoft textbook http://statsoft.com/textbook/stathome.html Good overview of methods and concepts
SAS manuals http://support.sas.com/onlinedoc/913/ Thorough overview of analysis procedures found in SAS
GraphPad http://graphpad.com/help/prism5/prism5help.html?usingstatistical_analyses_step_by_s.htm See the GraphPad statistical guide for easy introductions to many concepts in statistics
R http://cran.r-project.org/ The Comprehensive R Archive Network

Introduction to R

Exploratory data analysis

Hypothesis testing

http://bioinformatics.ca/workshops/2009/course-content 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 http://www.ploscompbiol.org/article/info:doi%2F10.1371%2Fjournal.pcbi.1000482 A Quick Guide to Teaching R Programming to Computational Biology Students
R reference card http://cran.r-project.org/doc/contrib/Short-refcard.pdf A reference card for R syntax
UCLA tutorials http://www.ats.ucla.edu/stat/r/ Useful example code while learning R
R vs. other languages http://www.johndcook.com/R_language_for_programmers.html A brief description of how R differs from other programming languages. Useful if you already know a programming language.
Which test do I use http://www.practicalstats.com/which/index.html An interactive guide to choosing which statistical test to use.
EMBNet Microarray course http://vit-embnet.unil.ch/CoursEMBnet/Arrays06/Material.html An online course with R/Bioconductor example tutorials
EMBNet tutorials http://www.ch.embnet.org/pages/courses2.html Other helpful tutorials with R examples related to biostatistics
SIB tutorials http://edu.isb-sib.ch/ Portal to the SIB bioinformatics tutorials - includes R, Unix, Perl, statisitics and lots more.
CBW tutorials http://bioinformatics.ca Portal to the Canadian Bioinformatics Workshop material. Includes R, statistics and lots more.
Microarrays
NMC http://www.mikromatrise.no/ Norwegian Microarray Consrtium
MACF http://core.rr-research.no/ UiO MicroArray Facility
Bioinformatics core facility http://core.rr-research.no/index.php?section=3 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
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
Structure
Networks
Required files [Sample network[1]] [Node atributes[2]] Please download these and uncompress before using
Cytoscape http://www.cytoscape.org/ Cytoscape home page
Cytoscape http://cytoscape.org/cgi-bin/moin.cgi/Presentations Tutorial on Cytoscape
Cytoscape http://cytoscape.wodaklab.org/wiki/How_to_increase_memory_for_Cytoscape Solution to common problem with working with large networks in Cytoscape.
iRefIndex Cytoscape plugin http://irefindex.uio.no/wiki/README_Cytoscape_plugin_0.9x iRefIndex installation
iRefIndex http://irefindex.uio.no iRefIndex wiki
iRefIndex publication http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=18823568 Full details of iRefIndex
DAVID http://www.nature.com/nprot/journal/v4/n1/pdf/nprot.2008.211.pdf Nature Protocols paper
GSEA http://www.broadinstitute.org/gsea/doc/subramanian_tamayo_gsea_pnas.pdf PNAS paper
GSEA http://www.broadinstitute.org/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.

https://sympa.uio.no/usit.uio.no/info/cbo-all

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

http://mailman.uib.no/listinfo/bioinfo.users.

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


Archived courses

http://donaldson.uio.no/wiki/Bioinformatics_for_molecular_biology_2010

http://donaldson.uio.no/wiki/Bioinformatics_for_molecular_biology_2009

Wiki help

http://excel2wiki.net/index.php

http://en.wikipedia.org/wiki/Help:Table