Systems Biology: Resources, standards and tools

Systems Biology requires a multidisciplinary skill base, and in order to perform research using systems biology approaches one should be familiar with a wide variety of systems biology related concepts originating from (molecular) biology, computational data integration, network-based analysis, mathematics, control theory and knowledge bases. The course therefore provides the student with a broad overview of the main concepts necessary to understand and use systems biology approaches in research. It introduces the students to the history of systems biology, the relationship between systems biology and high throughput genomics; the variety of data types and databases that are available for building systems networks; the importance of data standards and the use of specific data formats; he importance of 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; the Cytoscape platform.

After completing the course the student will be able to:

• Describe the reasons why systems biology was proposed and introduced as a new research approach, the main theories and concepts that it is founded on, and explain why these concepts have been important to establish it as an integrative biological research approach.
• Explain the fundamentals of graph-based, pathway-based, and computational model-based analysis and simulation. The student will be able to explain the value of text mining for information retrieval, and motivate the use of ontologies for data description and analysis, the use of standards, knowledge and data exchange formats for analysing experimental results, as well as the use of pathway-based analysis of omics data for setting up network-based analysis methods.

After completing the course the student will be able to:

• Use a range of standards, resources and tools available on the internet and combine them into approaches appropriate for their biological research, and be able to use curated information resources, and annotate and add new information to a network from literature curated by the student
• Find relevant background information related to a specific biological system or domain that they are working with.
• Skillfully apply network-based Systems Biology knowledge integration and analysis methods for the interpretation of new experimental results.
• Use a variety of software tools on the web to analyse experimental results/omics data in the context of available network and pathway knowledge, and use the results for network building.
• Exploit the different functions of the Cytoscape platform and more than a dozen of its main Applications, in setting up the different steps of building a biological network.
• Develop a comprehensive network-based systems biology approach for knowledge discovery to address specific biological questions, and use their knowledge to develop new research using systems approaches and design integrated analysis methods for interpreting their own results.

After completing the course the student will be able to:

• Contribute to innovative systems biology approaches in new biological research fields, and collaborate well in multidisciplinary projects.
• Report on systems biology studies and research findings and contribute to discussions about the applicability of new integration and analysis approaches in such projects.
• Find relevant systems biology-related research papers, and be able to use the findings in order to consider and design innovative new systems biology approaches for new applications in this field.

The course follows an Active Learning approach in which students collaborate in small groups to discuss and work with tasks and questions, based on teacher guidance. The material for the course comes from recent scientific review papers describing systems biology concepts, tools, approaches and resources.

A substantial part of the course is devoted to project-based learning in PC classes, in which the students will practice the use of tools, resources and data integration approaches to build a biological network, analyse it and use network-based approaches for integrated data and systems analysis. Using a gene list resembling an experimental outcome they build a network retrieving information from the web about the parts (genes, proteins) of biological networks, and use the Cytoscape platform 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.