A team of mathematicians is working on a theoretical and computational model of the body’s immune system, which will help advance the understanding as to how the body fights diseases among researchers associated with various scientific disciplines—such as immunologists, computer scientists, physicists, engineers etc.
The ‘Immunology Imaging and Modelling’ project is being funded by the Biotechnology and Biological Sciences. It is believed that the project will open the door for bringing together scientists working in different fields, who will then help bring about medical advances for patients.Scientists have yet to fully understand how the immune system works. Their understanding about the body’s immune responses can be enhanced by packaging various information about the immune system in a quantitative format, so that the entire scientific community may access it.
“A multi and cross-disciplinary, cohesive and active approach is urgently required. The ability to track parasites and cells in real time using novel imaging techniques is allowing exciting new insights and will help us measure the interactions between the different parts of the immune system. This will provide a theoretical and computational model of the immune system, giving a complete picture that researchers from across all disciplines can refer to and draw upon,” says Dr. Carmen Molina-Paris, network co-ordinator and researcher at the University of Leeds.
“Mathematical immunology is maturing into a discipline where modelling helps everyone to interpret data and resolve controversies. Most importantly, it suggests novel experiments allowing for better and more quantitative interpretations,” Dr. Molina-Paris added.
Steve Visscher, interim Chief Executive of BBSRC said: “The new insight that this model will provide will naturally benefit the patient with the advances in healthcare it will lead to. BBSRC is committed to developing an active and cohesive cross-disciplinary community at the mathematics biology interface to enable a more quantitative and predictive biology.”
The project has been reported in the quarterly research highlights magazine of the Biotechnology and Biological Sciences Research Council (BBSRC).
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