Course content

Systems Biology requires a multidisciplinary skill base, and to perform research using systems biology approaches one should be familiar with a wide variety of important concepts originating from (molecular) biology, computational data integration, network-based analysis, mathematics, control theory and knowledge bases. The course will provide the student with a broad overview of the main concepts necessary to understand and use systems biology approaches in research, and will introduce:

The history of systems biology, including some examples

Recent genomics-based technologies

The variety of data types and databases that are available
The importance of data standards and use of specific formats
The need for ontologies for description and analysis of biological data
The most important databases and software tools available on the web
Knowledge resources, portals – organism specific resources
Text mining and knowledge management
Data integration approaches
Graphs and networks
Pathway-based analysis
Cytoscape and CellDesigner
Basic modelling/simulation tools


The course will be given in the form of 14 lectures based on recent relevant scientific review papers describing systems biology concepts, tools, approaches and resources. The course includes 10 PC exercise sessions in which the students will practice the use tools and resources important for biological data integration, build a network retrieving information about the parts (genes, proteins) of biological networks, and use the public tools Cytoscape and CellDesigner for basic graph-based or pathway-based analysis of experimental data. The course will be relevant for molecular (cell) biology students and students from biotechnology and chemical engineering who are interested in systems biology.

Learning outcome

Kunnskaper
Students will be trained in the basics of Systems Biology. They will have an overview of the history of systems biology and how it became one of the approaches to study biological systems. They will know the essence of graph-based analysis; pathway-based analysis; computational model-based simulation and analysis; the importance of ontologies for data description and analysis; the use of standards and knowledge/data exchange formats; text mining; recent examples of omics technology development.
Ferdigheter:
Students will know how to find relevant background information related to a specific biological system or domain. They will have basic skills to use a variety of tools to analyse their experimental results in the context of available network and pathway knowledge. Students will have knowledge of the basic concepts that are relevant for systems biology approaches. They will be able to broadly understand systems biology-related research papers, and they have the skills to consider and design a systems biology approach for their own future experimental research.
General competense:
Students will have a thorough knowledge of current scientific concepts and approaches. They will be able to contribute innovative approaches to biological research, and collaborate well in multidisciplinary projects.

Learning methods and activities

Compulsory PC classes

Lectures will be in English, and based on recent relevant scientific review papers. In addition there will be 6 afternoons of PC-work, in which general web tools and public software will be used to retrieve knowledge about gene networks, and to combine various types of data to perform network and pathway-based analysis of the function of biological systems. A list of tasks will be performed and a written report on the findings will be submitted for review. Exams (written) are based on 16 – 20 questions that require short essay-type answers. Outside of the teaching period the written exam can be replaced by an oral exam.

Compulsory assignments

• Exercises

Recommended previous knowledge

Molecular Biology, molecular cell biology, biotechnology. Basic knowledge of statistics will be required.

Course materials

Scientific review papers, total of 250 pages.