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WIREs Syst Biol Med
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Aging and computational systems biology

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Aging research is undergoing a paradigm shift, which has led to new and innovative methods of exploring this complex phenomenon. The systems biology approach endeavors to understand biological systems in a holistic manner, by taking account of intrinsic interactions, while also attempting to account for the impact of external inputs, such as diet. A key technique employed in systems biology is computational modeling, which involves mathematically describing and simulating the dynamics of biological systems. Although a large number of computational models have been developed in recent years, these models have focused on various discrete components of the aging process, and to date no model has succeeded in completely representing the full scope of aging. Combining existing models or developing new models may help to address this need and in so doing could help achieve an improved understanding of the intrinsic mechanisms which underpin aging. WIREs Syst Biol Med 2016, 8:123–139. doi: 10.1002/wsbm.1328

An integrated overview of aging and some of its key players. This figure emphasizes the extent of interplay between the different components that underpin intrinsic aging, and how age‐related changes to these components affect health‐span and longevity. The integrated nature of this diagram highlights the complexities of aging and why computational models are needed to help study its dynamics. IGF‐1, insulin‐like growth factor‐1; ROS, reactive oxygen species; PARP, poly ADP ribose polymerase; mTOR, mammalian target of rapamycin.
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An Systems Biology Graphical Notation (SBGN) representation of the autonomic nervous system. The aim of this proposed model would be to simulate physiological responses associated with the autonomic nervous system such as heart rate, rate of movements in the gastrointestinal tract, or synthesis of B cells by the spleen. These processes are regulated in part by neurotransmitters and cytokines. Dysregulation of these processes together with oxidative stress have been strongly implicated in the pathology which underpins Parkinson's disease. NE, norepinephrine; 5HT, serotonin; Ach, acetylcholine.
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Integrating a computational model of cholesterol metabolism with a variety of other factors involved in the onset of cardiovascular disease (CVD). Our extended model is framed around the insidious rise in reactive oxygen species (ROS) that occurs with age. This rise in ROS is a key driver which underpins a pathological cascade that ultimately results in CVD. LDL‐C, low‐density lipoprotein cholesterol.
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In the Spotlight

Jens Nielsen

Jens Nielsen
is a Professor in the Department of Biology and Biological Engineering at Chalmers University of Technology in Göteborg, Sweden. His research focus is on systems biology of metabolism. The yeast Saccharomyces cerevisiae is the lab’s key organism for experimental research, but they also work with Aspergilli oryzae.

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