Algorithms in Bioinformatics
Teaching Winter Semester 2004/05 Bioinformatics Software Tools
 
Welcome
People
Research
Publications
Software
Talks
Teaching
  Winter Semester 2008/09
  Summer Semester 2008
  Winter Semester 2007/08
  Summer Semester 2007
  Winter Semester 2006/07
  Summer Semester 2006
  Winter Semester 2005/06
  Summer Semester 2005
  Winter Semester 2004/05
  Phylogeny
  Computational Sequence Analysis
  Selected Topics in Bioinformatics
  Bioinformatics Software Tools
  Summer Semester 2004
  Winter Semester 2003/04
  Summer Semester 2003
  Winter Semester 2002/03
  Summer Semester 2002
Bachelor Thesis/ Student Projects
Master Thesis/ Diploma Projects
Studienkommission
Contents
Search
Address
ZBIT
CS Dept.
University
 

Practical Course: "Bioinformatics Software Tools"


 
General Subject: Bioinformatik, Practical informatics
Tutors:
Tobias Dezulian, Christian Rausch und Prof. D. Huson
Time:
Oct. 5-15. 2004, 8:30-17:00
Amount: 4 SWS,  examinable: 2 SWS
Location: Computer room C311
Consulting Hour:
Thursday 5-6pm and by appointment
Home page: http://www-ab.informatik.uni-tuebingen.de/teaching/ws04/tool/welcome.html
Enrolement:
ab-toolsprak@informatik.uni-tuebingen.de
Description:
In this tutorial we want to look at several software tools that are widely used at the moment.
E.g.: Programs for sequence comarison (pairwise and multiple alignments, e.g. ClustalW, T-Coffee), programs for phylogenetic reconstruction (e.g. Phylip, Paup, SplitsTree), database search (e.g. BLAST, HMMer), vizualisation (e.g. CGViz), genefinding (e.g. genscan) and others.
Requirements for admission:
completed Vordiplom Bioinformatik, the lectures "Algorithms in Bioinformatics I and II" are recommended.



Course language

The teaching language is German or English if any participant does not understand German.
For written documents (hand-outs, protocols etc.) the language is English.

Summary

Day

Topic

1

microRNA: Theory intro, RFAM database, RNAfold, PSSM/PWM, SequenceLogo

2

EMBOSS Software Package: Tutorial, “Gaston's study of a human protein”
Working material:
pUC19.seq: sequence of a coloning vector in gcg format
Exercise: A study of a human protein

3

Multiple Sequence Alignments: Reminder on strategy, using + comparing clustalw, t-coffee, dialign, mucle, probcons to align protein sequences of G-Protein coupled receptors (GPCR), aligning human hemoglobin (a-chain), myoglobin and lupin leghemoglobin: despite the low mutual sequence identity (m-l 23%, h-l 15.6%) high structural similarity.

Using splitstree (jsplits) to reconstruct the phylogeny of the aligned GPCR.

Quick introduction to phylogeny; programming task: building gene-trees of genes that 8 given bacteria have in common (identifying “same” genes by their name...)

Questions on: COG database and EBI proteome

4

Answering questions on COG and EBI proteome, PAUP tutorial, VMD tutorial, visualizing 1AMU.pdb (Gramicidin Synthetase I A-domain, a NRPS), reveal its active site.

5

MODELLER, short intro, tutorial, homology modelling of 1AMU.pdb-homologs, comparing the modeled structure with the template structure.

Using HMMer (short intro to profile HMMs) to extract the A-domain of the NRPS for the homology modelling with 1AMU.

6

BLAST introduction based on Olaf's tex-slides, blasting two related bacterial genomes. CGViz intro (by Olaf), visualizing the blast-report with CGViz. Working through the CGViz tutorial. GCB04-talk “Syntenic layout of two assemblies of related genomes”. Using CGViz with the OSLay plug-in (implementation of the optimal syntenic layout algorithm by Daniel Richter) on the drosophila dataset.

7

CGViz with OSLay-plugin: understanding the different options, testing the software on different unfinished bacterial assemblies from genomesonline.org.

MUMmer: intro on suffix trees (including running time, space and search time complexity), using MUMmer (nucmer) to compare unfinished bacterial assemblies, rusult used as input for CGViz-OSLay.

8

SVMs: Intro: Florian Markowetz intro slides, reading + discussing two articles on protein sequence classification. Using the SVM implementation SVMlight to run the supplied example (text classification based on the Reuters dataset).

Running and evaluating SVMlight on the Wisconsin breast cancer data set.

9

Debriefing and concluding remarks, hand-out of the certificates of attendance (Scheine).



Download

All protocols (PDF, ~2 MB)





University of Tübingen