Systems Biology

Biological systems are highly intricate, functioning at various scales ranging from the molecular level (genes, RNAs, proteins, etc.) to the cellular, tissue, and organ levels (Tavassoly, Goldfarb et al. 2018). These multidimensional dynamical systems operate through complex interactions among their components, both in time and space (Tyson, Baumann et al. 2011). They possess the remarkable ability to adapt and maintain robustness under diverse conditions (Alon 2019). In contrast to reductionist classical approaches that focus on studying individual components in isolation, systems biology offers an approach to comprehensively understand biological systems at a holistic level (Dorvash, Farahmandnia et al. 2020). In recent years, systems biology has emerged as an interdisciplinary field, incorporating methodologies from network science, dynamical systems, mathematical modeling, machine learning, to Artificial Intelligence (AI) (Tavassoly, Goldfarb et al. 2018). By integrating these quantitative experimental frameworks, it aims to unravel the complexity of biological systems in terms of health and disease (Ideker, Galitski et al. 2001). The advent of omics technologies has played a pivotal role in propelling systems biology into a new era, allowing for the construction of in-silico models based on extensive in-vitro, in-vivo, and clinical data (Auffray, Chen et al. 2009). Furthermore, computational and mathematical platforms have been instrumental in extracting meaningful signals from the vast amounts of noise present in these large datasets (Kitano 2002; Tavassoly 2015). Through its advancements, systems biology has revolutionized medicine, enabling the shift toward precision and personalized medicine. By quantitatively dissecting biological processes, it has transformed medicine into a discipline that embraces the intricacies of individual variation. This chapter serves to review the history, methodologies, and applications of systems biology, highlighting its novel aspects and contributions to the field.