Systems biology is an emerging research agenda, which aims to characterise the functional properties of biological systems in terms of the integrated action of interacting networks of genes, proteins and biochemical reactions that respond to the environment. The systems biology of whole-organism physiology is however, so far relatively undeveloped. compbio.org brings together an interdisciplinary team of animal scientists, computer scientists and mathematicians around some challenging scientific problems. We seek to contribute to the life sciences, to systems biology and to the modeling disciplines of mathematics and computing.
We aim to exploit a uniquely rich in vivo data set, obtained from female rats, to undertake a systems biology study of the transition from pregnancy to lactation. This is a major systemic metabolic perturbation for the animal, involving several different tissue types, including adipose tissue (body fat), the liver, mammary gland and brain. These changes are orchestrated by hormonal responses, and ultimately at the genetic level. Much of the work in systems biology has focused on describing the kinetics and flow of elements through a system using mathematical and computational models. We are building such models in the physiological context of interest, in particular looking at the kinetics of triglicerides (fats). To obtain a more complete analysis of biological systems however, a modeling approach must be developed that integrates the structural and dynamic components of the system at multiple scales. This requires a higher level, 'engineering' perspective. Computer scientists, specifically software engineers, have developed a powerful set of concepts and techniques for modeling embedded, real-time and reactive systems. We will investigate how this approach, used in conjunction with mathematical modeling, may be brought to bear in studying the systems biology of this important physiological system.
The consortium is based on a collaboration between
Michigan State University [MSU] and
University College London [UCL] but is open to engagement from across the scientific community. Participation at MSU is drawn from the
Department of Animal Science and the
Department of Computer Science & Engineering and accesses researchers from the
Quantitative Biology Initiative [QBI]. Participation at UCL is drawn from the
Department of Mathematics and the
Department of Computer Science working through the
Centre for Mathematics and Physics in the Life Sciences and Experimental Biology [CoMPLEX]. We are also collaborating with
University of Granada through the
Concurrent Systems Research Group.
If you have any questions, would like further information or would like to work with us, please email either
Theresa Casey or
Anthony Finkelstein.
