Systems biology

Systems biology is the computational and mathematical analysis and modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach (holism instead of the more traditional reductionism) to biological research.^[1] This multifaceted research domain necessitates the collaborative efforts of chemists, biologists, mathematicians, physicists, and engineers to decipher the biology of intricate living systems by merging various quantitative molecular measurements with carefully constructed mathematical models. It represents a comprehensive method for comprehending the complex relationships within biological systems. In contrast to conventional biological studies that typically center on isolated elements, systems biology seeks to combine different biological data to create models that illustrate and elucidate the dynamic interactions within a system. This methodology is essential for understanding the complex networks of genes, proteins, and metabolites that influence cellular activities and the traits of organisms.^[2]^[3] One of the aims of systems biology is to model and discover emergent properties, of cells, tissues and organisms functioning as a system whose theoretical description is only possible using techniques of systems biology.^[1]^[4] By exploring how function emerges from dynamic interactions, systems biology bridges the gaps that exist between molecules and physiological processes.

As a paradigm, systems biology is usually defined in antithesis to the so-called reductionist paradigm (biological organisation), although it is consistent with the scientific method. The distinction between the two paradigms is referred to in these quotations: "the reductionist approach has successfully identified most of the components and many of the interactions but, unfortunately, offers no convincing concepts or methods to understand how system properties emerge ... the pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration with mathematical models." (Sauer et al.)^[5] "Systems biology ... is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different. ... It means changing our philosophy, in the full sense of the term." (Denis Noble)^[6]

The central flow of biological information and the corresponding omics fields, emphasizing the systems biology approach of integrating genomics, transcriptomics, proteomics, and metabolomics to link genotype to phenotype.

As a series of operational protocols used for performing research, namely a cycle composed of theory, analytic or computational modelling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory.^[7] Since the objective is a model of the interactions in a system, the experimental techniques that most suit systems biology are those that are system-wide and attempt to be as complete as possible. Therefore, transcriptomics, metabolomics, proteomics and high-throughput techniques are used to collect quantitative data for the construction and validation of models.^[8]

A comprehensive systems biology approach necessitates: (i) a thorough characterization of an organism concerning its molecular components, the interactions among these molecules, and how these interactions contribute to cellular functions; (ii) a detailed spatio-temporal molecular characterization of a cell (for example, component dynamics, compartmentalization, and vesicle transport); and (iii) an extensive systems analysis of the cell's 'molecular response' to both external and internal perturbations. Furthermore, the data from (i) and (ii) should be synthesized into mathematical models to test knowledge by generating predictions (hypotheses), uncovering new biological mechanisms, assessing the system's behavior derived from (iii), and ultimately formulating rational strategies for controlling and manipulating cells. To tackle these challenges, systems biology must incorporate methods and approaches from various disciplines that have not traditionally interfaced with one another.^[9] The emergence of multi-omics technologies has transformed systems biology by providing extensive datasets that cover different biological layers, including genomics, transcriptomics, proteomics, and metabolomics. These technologies enable the large-scale measurement of biomolecules, leading to a more profound comprehension of biological processes and interactions.^[10] Increasingly, methods such as network analysis, machine learning, and pathway enrichment are utilized to integrate and interpret multi-omics data, thereby improving our understanding of biological functions and disease mechanisms.^[11]

^ ^a ^b Tavassoly, Iman; Goldfarb, Joseph; Iyengar, Ravi (2018-10-04). "Systems biology primer: the basic methods and approaches". Essays in Biochemistry. 62 (4): 487–500. doi:10.1042/EBC20180003. ISSN 0071-1365. PMID 30287586. S2CID 52922135.
^ MacLeod, Miles; Nersessian, Nancy J. (2016-10-01). "Interdisciplinary problem- solving: emerging modes in integrative systems biology". European Journal for Philosophy of Science. 6 (3): 401–418. doi:10.1007/s13194-016-0157-x. ISSN 1879-4920.
^ Veenstra, Timothy D. (February 2021). "Omics in Systems Biology: Current Progress and Future Outlook". Proteomics. 21 (3–4): e2000235. doi:10.1002/pmic.202000235. ISSN 1615-9853. PMID 33320441.
^ Longo, Giuseppe; Montévil, Maël (2014). Perspectives on Organisms: Biological time, Symmetries and Singularities. Lecture Notes in Morphogenesis. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-35938-5. ISBN 978-3-642-35937-8.
^ Sauer, Uwe; Heinemann, Matthias; Zamboni, Nicola (2007-04-27). "Getting Closer to the Whole Picture". Science. 316 (5824): 550–551. doi:10.1126/science.1142502. ISSN 0036-8075. PMID 17463274.
^ Noble, Denis (2009). The music of life: biology beyond the genome (Repr ed.). Oxford: Oxford Univ. Press. ISBN 978-0-19-929573-9.
^ Kholodenko, Boris N.; Bruggeman, Frank J.; Sauro, Herbert M. (2005), Alberghina, Lila; Westerhoff, H.V. (eds.), "Mechanistic and modular approaches to modeling and inference of cellular regulatory networks", Systems Biology, vol. 13, Berlin/Heidelberg: Springer-Verlag, pp. 143–159, doi:10.1007/b136809, ISBN 978-3-540-22968-1, retrieved 2025-05-02
^ Romualdi, Chiara; Lanfranchi, Gerolamo (2009), Krawetz, Stephen (ed.), "Statistical Tools for Gene Expression Analysis and Systems Biology and Related Web Resources", Bioinformatics for Systems Biology, Totowa, NJ: Humana Press, pp. 181–205, doi:10.1007/978-1-59745-440-7_11, ISBN 978-1-934115-02-2, retrieved 2025-05-02
^ Bruggeman, Frank J.; Westerhoff, Hans V. (January 2007). "The nature of systems biology". Trends in Microbiology. 15 (1): 45–50. doi:10.1016/j.tim.2006.11.003. PMID 17113776.
^ Dhillon, Bhavjinder K.; Smith, Maren; Baghela, Arjun; Lee, Amy H. Y.; Hancock, Robert E. W. (2020-07-30). "Systems Biology Approaches to Understanding the Human Immune System". Frontiers in Immunology. 11: 1683. doi:10.3389/fimmu.2020.01683. ISSN 1664-3224. PMC 7406790. PMID 32849587.
^ Pazhamala, Lekha T.; Kudapa, Himabindu; Weckwerth, Wolfram; Millar, A. Harvey; Varshney, Rajeev K. (July 2021). "Systems biology for crop improvement". The Plant Genome. 14 (2): e20098. doi:10.1002/tpg2.20098. ISSN 1940-3372. PMID 33949787.

[Tavassoly_487–500-1] Tavassoly, Iman; Goldfarb, Joseph; Iyengar, Ravi (2018-10-04). "Systems biology primer: the basic methods and approaches". Essays in Biochemistry. 62 (4): 487–500. doi:10.1042/EBC20180003. ISSN 0071-1365. PMID 30287586. S2CID 52922135.

[2] MacLeod, Miles; Nersessian, Nancy J. (2016-10-01). "Interdisciplinary problem- solving: emerging modes in integrative systems biology". European Journal for Philosophy of Science. 6 (3): 401–418. doi:10.1007/s13194-016-0157-x. ISSN 1879-4920.

[3] Veenstra, Timothy D. (February 2021). "Omics in Systems Biology: Current Progress and Future Outlook". Proteomics. 21 (3–4): e2000235. doi:10.1002/pmic.202000235. ISSN 1615-9853. PMID 33320441.

[4] Longo, Giuseppe; Montévil, Maël (2014). Perspectives on Organisms: Biological time, Symmetries and Singularities. Lecture Notes in Morphogenesis. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-35938-5. ISBN 978-3-642-35937-8.

[5] Sauer, Uwe; Heinemann, Matthias; Zamboni, Nicola (2007-04-27). "Getting Closer to the Whole Picture". Science. 316 (5824): 550–551. doi:10.1126/science.1142502. ISSN 0036-8075. PMID 17463274.

[6] Noble, Denis (2009). The music of life: biology beyond the genome (Repr ed.). Oxford: Oxford Univ. Press. ISBN 978-0-19-929573-9.

[7] Kholodenko, Boris N.; Bruggeman, Frank J.; Sauro, Herbert M. (2005), Alberghina, Lila; Westerhoff, H.V. (eds.), "Mechanistic and modular approaches to modeling and inference of cellular regulatory networks", Systems Biology, vol. 13, Berlin/Heidelberg: Springer-Verlag, pp. 143–159, doi:10.1007/b136809, ISBN 978-3-540-22968-1, retrieved 2025-05-02

[8] Romualdi, Chiara; Lanfranchi, Gerolamo (2009), Krawetz, Stephen (ed.), "Statistical Tools for Gene Expression Analysis and Systems Biology and Related Web Resources", Bioinformatics for Systems Biology, Totowa, NJ: Humana Press, pp. 181–205, doi:10.1007/978-1-59745-440-7_11, ISBN 978-1-934115-02-2, retrieved 2025-05-02

[9] Bruggeman, Frank J.; Westerhoff, Hans V. (January 2007). "The nature of systems biology". Trends in Microbiology. 15 (1): 45–50. doi:10.1016/j.tim.2006.11.003. PMID 17113776.

[10] Dhillon, Bhavjinder K.; Smith, Maren; Baghela, Arjun; Lee, Amy H. Y.; Hancock, Robert E. W. (2020-07-30). "Systems Biology Approaches to Understanding the Human Immune System". Frontiers in Immunology. 11: 1683. doi:10.3389/fimmu.2020.01683. ISSN 1664-3224. PMC 7406790. PMID 32849587.

[11] Pazhamala, Lekha T.; Kudapa, Himabindu; Weckwerth, Wolfram; Millar, A. Harvey; Varshney, Rajeev K. (July 2021). "Systems biology for crop improvement". The Plant Genome. 14 (2): e20098. doi:10.1002/tpg2.20098. ISSN 1940-3372. PMID 33949787.

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