27040 Introduction to Systems Biology
|Introduktion til Systembiologi|
Point( ECTS )
Taught under open university
|E4B (Fri 8-12)
Scope and form:
|Lectures and exercises|
Duration of Course:
|E3B, Decide with teacher|
Type of assessment:
Not applicable together with:
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.
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
- 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
- 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
- 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
• 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
• Navigate in the KEGG and NCBI databases and extract relevant
• 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
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Last updated: 23. december, 2014