Welcome to MyCIB
The Multidisciplinary Centre for Integrative Biology (MyCIB) is a collaborative department that provides a cross-disciplinary environment across multiple disciplines. MyCIB provides a versatile computing infrastructure and data analysis support for post-genomic and integrative systems biology researchers. MyCIB provides a service for analysing datasets through collaboration with multiple biological groups for extra support with systems approaches. A systems-based approach ranges from mathematical modelling of a system, bioinformatics-based analysis and network biology. Therefore, the umbrella of the term systems biology is covered in the remit of the MyCIB group.
The figure above shows the many disciplines involved in the field of systems biology. The disciplines include a cycle of model production by the modeller based on data from biologists, mathematicians, chemists, computer scientists, physicists and engineers. The model then undergoes a cycle of evaluation and testing, which feeds back into the original model.
Integrative Systems Biology
Integrative Systems biology advances our understanding of biological phenomena through the close collaborative efforts of laboratory and theoretical scientists, who develop mechanistic mathematical models that identify gaps in biological knowledge and propose hypotheses for laboratory testing. The laboratory results lead iteratively to refined models that have predictive value, such as the interactions between diet and health, or improving drug efficacy while minimizing adverse reactions. The modelling integrates phenomena at different physical scales or incorporates different branches of physics (e.g. biochemical thermo-dynamics, with fluid dynamics and materials science). The approach is analogous to that between experimental and theoretical physicists.
The field of Network Biology, which comprises of holistic networks including metabolic, protein interaction and gene regulatory networks.
Holistic networks contain information of all the interactions within a system, which provides a structure to map on transcriptomics and metabolic data. Network properties and topology use graph theory to extract meaningful relationships or patterns within a network. For example, a hub is a highly interconnected node within a network. Therefore, if that hub is up-regulated, it can have a far larger affect on the system.
The figure above is an Arabidopsis KEGG metabolic network containing 2940 nodes and 4061 edges. The nodes are metabolites, reaction identifiers and genes. This network is visualised and analysed using Cytoscape software.