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27040 Introduction to Systems Biology

Danish title:

Introduktion til Systembiologi


Point( ECTS )


Course type:

Taught under single-course student


E4B (Fri 8-12)


Campus Lyngby

Scope and form:

Lectures and exercises

Duration of Course:

13 weeks

Date of examination:

E4B, Decide with teacher

Type of assessment:

Exam duration:



Not applicable together with:

Recommended prerequisites:


Participants restrictions:

Minimum 10

General course objectives:

To give the students both theoretical and practical experience with why, when and how to apply a network biology analysis approach to a given molecular biology problem.

This course gives a hands-on introduction to the Network Biology part of Systems Biology. The MSc course 27041 covers the mathematical modeling part of Systems Biology.

Learning objectives:

A student who has met the objectives of the course will be able to:
  • Apply a network biology analysis approach to a wide rage of molecular biology problems.
  • Describe the main high-throughput experimental methods used for generating protein-protein interaction data.
  • Critically assess the quality of high-throughput protein-protein interaction data.
  • Apply basic graph-theory based measurements on biological networks.
  • Describe basic computational methods for reconstructing and scoring biological networks based on high-throughput data.
  • Describe and apply basic algorithms for identifying likely protein complexes from protein-protein interaction data (MCODE).
  • Use the network visualization/analysis software CytoScape as a platform for integrative network based analysis.
  • Infer likely biological function of “orphan” proteins by analysis of their interaction partners.
  • Extract relevant information from the KEGG and NCBI databases
  • Describe how flucturations in metabolite pool sizes can affect gene expression profiles


• Introduction to Systems Biology, the motivation for applying a Systems Biology / Network Biology point of view to molecular biology problems.
• Experimental data behind protein-protein interaction networks. Pros and cons of different technologies.
• Network analysis: topology based scoring of interactions, basic understanding of key network parameters, and algorithms for identification of sub-networks.

Yeast Systems Biology – case: Cell cycle
• Introduction to core components of cell cycle regulation.
• Visualizing cell cycle regulatory networks.
• Introduction to transcriptomics data – how to overlay expression data with networks.
• Combining temporal (time-series) expression data with molecular networks, to discover modes of regulation.

Biomedical research – case: human heart development and diseases
• Introduction to the disease case: genetic defects, heart embryonic development and adult heart disease.
• Combining protein-protein interaction data from multiple species to form an inferred human interactome.
• The concepts of virtual pulldowns and relevance scored networks (0th and 1st order filtering).
• Tissue specific data: Molecular networks related to specific anatomical regions of the heart.

Bacterial Systems Biology: Proteomics, transcriptomics and metabolomics of bacterial systems
• Mass spec as part of the Systems Biology toolbox.
• Using pathways and network information to understand metabolic processes.
• Navigate in the KEGG and NCBI databases and extract relevant information
• Combine transcriptomics and metabolomics data to gain understanding of the biochemistry of a gene regulatory system

Green challenge participation:

Please contact the teacher for information on whether this course gives the student the opportunity to prepare a project that may participate in DTU´s Study Conference on sustainability, climate technology, and the environment (GRØN DYST). More infor http://www.groendyst.dtu.dk/english


27 Department of Systems Biology

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Last updated: 17. juli, 2015