Teaching

Courses in Systems Biology and Bioinformatics:

Study the small, be part of something great

Winter semester 2009/2010 Modelling and Simulation with Applications to the Life Sciences (Systems Biology - SB I) (Prof. Olaf Wolkenhauer, Dr. Thomas Millat, Dr. Julio Vera) Modul Nr. 23146 (follow-up lecture: BioSystems Modelling and Simulation (SB II), Modul Nr. 23147) Practical lectures: 22.01 and 26.01, Ulmenstr. 69, Haus 3, SR 422 Lecture: Tuesdays 7:30 - 9:00 Albert-Einstein-Strasse 21, Room 312 Tutorial: Fridays 13:00 - 15:00 Ulmenstr. 69, Haus 3, SR 120 Research Seminar (Systems Biology/Bioinformatics Group) Modul Nr. 23307 Seminar: Tuesdays 13:00 - 15:00 Ulmenstraße 69, Haus 2, SR 310 Kategorientheorie (Prof. Dr. Clemens H. Cap, Prof Olaf Wolkenhauer) Modul Nr. 23421 Wednesday 13:00 - 15:00 Albert-Einstein-Strasse 21, Raum 311 Komplexe Software Systeme (KSWS): Data Integration, Mining and Visualisation Modul Nr. 23177   Tuesdays 17:00-19:00 Albert Einstein Straße 21, Room 022 (old library)

See our Teaching -Flyer:

• Poster about the Chair in Systems biology and Bioinformatics
• 13 Gründe Bioinformatik und Systembiology zu studieren (13 Reasons to study Bioinformatics and Systems Biology, 1.7 MB pdf file)
• Rostock University cinema ad (uni-Trailer.wmv)
• Prospective Students: Consider our courses as part of the Masters in Computational Engineering

Recent technological and methodological developments in the biological- and medical-sciences, in the biotech- and pharma-industries enable us to gain a better understanding of the genetic origins and molecular processes that are at the root of development and disease. The areas of Bioinformatics and Systems Biology exemplify the way traditional scientific and engineering disciplines are being transformed to face the challenges arising from the revolutionary developments in the life sciences.

The area of Bioinformatics is concerned with the analysis of biological information; providing tools and techniques for the interpretation of data. A major challenge is the integration and interpretation of biological data that are generated by a range of technologies including, for example, DNA and protein sequences; gene/protein expression data from microarrays or gene-chips; changes in the proteome assessed through immunoblotting or 2D gels; or protein peptide masses obtained from mass spectrometry. The analysis of gene information within a genome; comparisons between genome sequences; and structural properties of proteins provide information about gene/protein interaction networks underlying basic cell functions. More recently, Systems Biology has emerged as an integrative approach that investigates inter- and intra-cellular networks through mathematical modeling and simulation.

Our courses offer a solid basis for jobs in industry and academia, covering fundamental techniques in data analysis, mathematical modelling and simulation. You will be able to join interdisciplinary and international teams in what is widely considered the most important research field -- life sciences. Our courses provide a launch pad for a careeer in biomedicine and biotechnology.

Unsere Vorlesungen werden in zwei Masters Studiengängen angeboten: Dem Masters in Computational Engineering (Faculty for Computer Science and Electrical Engineering) and Medizinische Biotechnologie (Medical Faculty)

We offer a range of projects from undergraduate to postgraduate level, covering problems in software development, data mining, visualisation, modelling and simulation. Projects can be conducted 'in-house' or with national and international partners. We are also able to support successful students with industrial placements in Germany, Europe and overseas. See the Project Page for further information. Contact Prof. Wolkenhauer any time for further information. (Room 315, Albert Einstein Str. 21).

Informationen fuer Studenten der Informatik

Note for students on the MSc "Computational Engineering"

The Systems Biology course, complemented with tutorial classes and lectures on SB/BI tools, focusses on methodologies for modelling and simulation of dynamic systems. In the classes we are going to concentrate mostly on stochastic models and differential equation models. These concepts are generic and widely applicable in the physical- and engineering sciences. Motivated by the advances and opportunities for interdisciplinary research in biotechnology and the life sciences, the examples and exercises are choosen from molecular and cell biology. No prior training in molecular biology or biochemistry is required. All that is needed is an interest in interdisciplinary training. To complement the somewhat more abstract material with practical training we also introduce simulation tools and programming languages. The bioinformatics classes on the other hand complement systems biology in that information resources, databases and algorithms are surveyed. On Tuesday our group organises weekly research seminars that provide an opportunity to learn more about current research in the life sciences and opportunities for the physical and engineering sciences.

• Modul discription - Modelling and Simulation with Application to the Life Sciences
  
  
• Modul discription - BioSystems Modelling and Simulation
  
  
• Modelling and Simulation with Applications to the Life Sciences
  
  • Short list of keywords and topics:
    • Biochemical reaction networks
    • Systems theory
    • Experimental data generation
    • Modelling biochemical reactions
    • Stochastic modelling and simulation
    • Nonlinear dynamics
    • Pathway modelling
    • Feedback regulation and control
    • Tools and databases
  • Recommended literature:
    • Detailed recommendations for the literature are part of the lecture notes.
    • For non-biologists the following textbooks are recommended:
      • Bruce Alberts et al.: Molecular Biology of the Cell. Garland Science. (Do not buy the German translation)
      • Franklin M. Harold: The Way of the Cell. Oxford University Press.
      • Aydin Tözeren et al.: New Biology for Engineers and Computer Scientists. Pearson Prentice Hall Bioengineering.
  • Course material:
    • Systems Biology - lecture notes (6.2MB, for students of this course only!)
    • Basics of molecular biology. Part 1
    • Basics of molecular biology. Part 2
    • Basics of molecular biology. Part 3
    • Basics of Systems Theory. Part 1
    • Basics of Systems Theory. Part 2
    • Power-law models. Part 1
    • Power-law models. Part 2
    • Additional Document: Power-law models in cell signalling
    • Matlab file with simulations. File 1
    • Matlab file with simulations. File 2
    • Other mathematical models
    • Additional document:Stoichiometric models
    • Additional document: models in PDE
    • Additional document: DEB models
    • Additional Document: 45 pages introduction to Molecular Biology for Computer scientists.
    • Computational models
    • Additional document: Executable cell biology
    • Advanced Concepts in Systems Biology
    • Additional document: Iterative Systems Biology
    • Additional document: Other analytical tools
    • An introduction to the modelling tools of Systems Biology
    • JAK2-STAT5 signalling
    • JAK2-STAT5 signalling. Additional document
    • Practical lecture of Systems Biology I
    • Practical lecture of Systems Biology II
    • Addtional document: SBML files for SYCAMORE
    • Stochastic modelling of biochemical systems

• BioSystems Modelling and Simulation
  
  • Short list of keywords and topics:
    • Nonlinear systems theory
    • Cell signalling
    • Dynamic motifs and modules
    • Approximations in the modelling of biological reaction networks
    • Automata models
    • Cell functions
    • Receptor modelling
    • Cell cycle models
    • Receptor modelling
    • Computational cell biology
    • Metabolic control analysis
  • Recommended literature:
    • Detailed recommendations for the literature are part of the lecture notes.
  • Course material:
    • Bistable Systems
    • Transport Mechanisms
    • Quantitative Measures
    • Petri Nets
    • Stochastic Modelling of Cell Cycle
    • Why Stochastic Modelling?

• Current Research in Bioinformatics and Systems Biology (research seminar)
  • Bioinformatics and Systems Biology are rapidly growing new interdisciplinary research fields. They cover a wide range of topics from computer science, physics, mathematics, chemistry, and engineering which are applied in the life sciences. This includes such questions like: physical description of biosystems, mathematical methods in analysis of biosystems, databases and data management in biology, visualisation of biological information, and philosophical aspects of natural sciences.
  • These weekly seminars are a mix of presentations from within the group, students, and academic visitors.
  • Dates and Topics

• Proseminar: Artificial Life, Artificial Intelligence
  • Virtual Cells: Can we simulate life?
  • Artificial Intelligence: Can computers think?
  • Roger Penrose: Is the brain a computer?
  • Daniel C. Dennet: Free will and cellular automata.
  • Stephen Wolfram: A new kind of science?
  • The Matrix: Is our reality a simulation?
  • Chess & Go: Complexity emerging from simplicity.
  • Topics

• Komplexe Software Systeme (KSWS): Data Integration, Mining and Visualisation
  • Students work in groups on modules of a larger software project that is concerned with current research topics in Bioinformatics and Systems Biology. Design of new software tools as well as enhancement of existing packages can be part of the project.

   

The material provided here is for the use of registered students taking my courses and in preparation for their exams only. Any other use is not allowed without permission.

• Resources & Key papers
• Video lectures
• Tipps zum Schreiben eines englischen Lebenslaufs
• Guidelines for marking reports and presentations
• Data Engineering (MSc Advanced Control & Systems Eng.)
• Data Handling (BSc Biochemistry, BSc Biological Sciences, BSc Bioinformatics)