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.

• 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.

Introduction:
• 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.

Metabolic engineering
• Using pathways and network information to alter and optimize metabolic processes.
• Mass spec as part of the Systems Biology toolbox.

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 information http://www.groendyst.dtu.dk/kursustilmelding.aspx