Examplepictures of DNA-Structures

Topics for Theses

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Summer term courses

Winter term courses


Applied Bioinformatics

  • Introduction
  • Databases, Tools, and Web resource
  • Sequence comparison
  • Phylogeny
  • Protein Structure

The applied bioinformatics module introduces basic concepts of applied bioinformatics. It starts with a brief overview of molecular biology, the role of bioinformatics, and available data archives. Next, sequence comparison and protein structure are introduced and major databases, tools, and online resources are covered. Curation, annotation and quality control of data is discussed. The module covers sequence comparison in depth starting with dot plots from which the basic dynamic programming alogorithms for sequence alignment are derived. These are extended to include penalties, rewards and substitution matrices. Finally, the realisation of these techniques in Blast is discussed including the assessment of significance of results. Multiple alginments and profiles are briefly mentioned. The above methods are then used in the context of sequence-based phlogentic analysis and character- and distance-based methods are introduced. Regarding protein structure basic concepts of protein stability and folding, structure alignments structure evolution, structure classification, and structure prediction and modelling are introduced.

  • Students will be able to use online resources to answer biological questions
  • Students will have a basic understanding of complexity of data
  • Students will be able to apply the basic analysis techniques
  • Students will be able to critically assess quality of analysis

Programming for Bioinformatics

  • Introduction
  • Relational Databases
  • Python

The module programming for bioinformatics (bioinformatics II) will teach students basic programming skills relevant to bioinformatics, which will enable them to actively develop bioinformatics tools. The module will take a problem-driven approach. It will present bioinformatics problems and show how to solve them using existing online tools and how to implement such tools. Students will revisit some of the problems and databases discussed in applied bioinformatics. The students will be exposed in a very practical and hands-on approach to basic computer science tools such as using command line operating systems, programming in Python, and using relational databases. They will apply these skills to solve bioinformatics problems.

  • Students will have an understanding of different operating systems
  • Students will be able to automate simple repretitive information retrieval tasks
  • Students will be able to write simple programs in Python
  • Students will be able to work with relational databases
  • Students will appreciate the principles, limits, and possibilities of programming
  • Students will be able to formulate biological questions as information processing problems
  • Students will understand when and how programming can help to automate bioinformatics problems

Algorithmic Bioinformatics

The algorithmic bioinformatics module (bionformatics III) covers algorithmithms for bioinformatics. Bioinformatics I and II are needed as basis. The module covers algorithms and data structures for bioinformatics. It breaks down into three parts: Algorithms for sequences (sequence alignment, multiple sequence alignment, phylogenetic trees, scoring matrices, patterns and motifs), structures (structure alignment with double dynamic programming and clustering), and advanced topics such as gene expression data analysis, docking, threading, textmining, image analysis.

  • Students will have an understanding of the topics covered
  • Students will be able to design data structrures and algorithms to analysis bioinformatics data
  • Students will be able to critically assess quality of algorihtms
  • Students will be able to write basic programmes

Reading list

The modules closely follow textbooks:

  • Applied bioinformatics: Lesk. Introduction to Bioinformatics, Oxford University Press, 2002. You can download chapter 1 of the book.
  • Programming for Bioinformatics: You need two books: one on databases (e.g. MySQL Cookbook by Paul DuBois, O'Reilly or MySQL by Paul DuBois, Michael Widenius, O'Reilly) and one on programming with Python (we will follow some online material as well as Python in a Nutshell by Alex Martelli, O'Reilly). Note, on O'Reilly's Python section you get online access to some chapters of their python books, which might be useful to get quick access. We also aquired a copy of Web Programming in Python by George K. Thiruvathukal, et al, Prentice Hall. Although geared towards web programming, it contains a nice overview of Python basics and database work. Last but not least we suggest How to Think Like a Computer Scientist by Allen B. Downey et. al which is completely open source.
  • Algorithmic Bioinformatics: Eidhammer, Jonassen, Taylor. Protein Bioinformatics: An algorithmic approach to sequence and structure analysis. Wiley

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