Current State-of-The-Art and Future Directions in Systems Biology

Si Chen, Ali Ansari, William Sterrett, Kate Hurley, Jeremy Kemball, Jared C Weddell, P I Imoukhuede


Systems Biology offers the promise of decoding genetic information, optimizing pharmaceutical design, and aiding in the development of precision medicine. These advances require the bimodal approach of deriving information from experimental data and integrating such information via computational modeling. However, choosing an appropriate experimental assay and computational model is paramount to the accuracy and relevancy of the output. Here, we delve into the fundamental concept of several commonly used modeling approaches, their advantages and limitations, as well as potential applications. We review and compare experimental assays used in systems biology, based on the throughput, simplicity and possibility for quantification. In addition, we review current experimental models used in conjunction with assays to provide parameters and/or validation for computational modeling. Lastly, we present applications of systems biology in medicine: case studies, clinical opportunities, and future directions of systems biology


computational modeling; high-throughput; deterministic; stochastic; agent-based; qFlow cytometry

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