The November breakfast seminar will be about mathematical modelling of animal physiology and will be given by Assoc. Prof. Susanna Röblitz, who recently started her research group at the Computational Biology Unit.
Modern dairy industry relies on cows bred to produce up to 40 liters of milk per day. However, concurrent with a selection for increased milk yield, a decrease in dairy cow fertility has been observed during the last decades. New strategic directions for genetic selection including fertility-related traits will take time to be effective. Therefore, alternative strategies are indispensable to obtain immediate improvements. Though progress has been made in reproductive management, a cohesive systems biology approach to the control of reproduction in dairy cows was missing. Mathematical modelling of the involved mechanisms gives insights into the underlying biological processes, and thereby helps to overcome the antagonistic relationship between milk yield and reproductive performance. In this talk, I will present our results on constructing a dynamic, mathematical systems model of nutritional and physiological control of reproductive processes in dairy cattle. Our approach is different to many other systems biology approaches in that we have constructed a model on the whole organism level instead of focusing on cellular mechanisms, which requires an understanding at a rather high biological level of organization. This research is an early attempt towards the in silico development of strategies for diagnosis and treatment with the aim to refine and reduce animal experiments.
"Digital Frukost" is an open breakfast seminar series focusing on research activities at the interface between the biological sciences and that of mathematics, computer science, physics or engineering. Examples of such research activities could be mathematical or computational modeling of biological systems, application of engineering/control systems theory on biological systems or inspired by biological systems, application of mathematics/statistics/machine learning to analyze big data in health or marine sector; from sensor systems, imaging or omics technologies etc.
We hope to see many of you there!
As food will be served, please register your attendance using this link.