# Systems biology

### Systems biology

Methodology developed to understand how biological functions arise from multiple and complex interactions among many molecules and cells [1]. Network data are typically obtained with high-throughput data from whole-tissue [2], and single-cell omics [3], co-expression analysis [4], and protein-to-protein identification with two-hybrid assays [5]. Statistical tools include a plethora of mathematical analysis and computerized modeling, ranging from data‐driven methods that aim to identify ‘patterns’, ‘clusters’, ‘correlations’, and ‘topology’, from experimental data [6] (e.g., principal component decomposition methods, supervised classification, linear/nonlinear regression methods, graph analysis, Bayesian networks, persistent homology), to model‐driven methods that aim, instead, to reconstruct networks that can be used in simulations (e.g., machine-learning classifiers, time series analysis, deterministic and stochastic differential equations) (reviewed in [7]).

*McGillivray, P., Network Analysis as a Grand Unifier in Biomedical Data Science. Annual Review of Biomedical Data Science, 2018.***1**.*Pardo, L., et al., Targeted activation of CREB in reactive astrocytes is neuroprotective in focal acute cortical injury. Glia, 2016.***64**(5): p. 853-74.*Pardo, L., et al., CREB Regulates Distinct Adaptive Transcriptional Programs in Astrocytes and Neurons. Sci Rep, 2017.***7**(1): p. 6390.*Zhang, B. and S. Horvath, A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol, 2005.***4**: p. Article17.*Aloy, P. and R.B. Russell, Interrogating protein interaction networks through structural biology. Proceedings of the National Academy of Sciences of the United States of America, 2002.***99**(9): p. 5896-5901.*Bielza, C., Larrañaga, P. , Data-Driven Computational Neuroscience. 2020: Cambridge University Press.**Wang, R.S., B.A. Maron, and J. Loscalzo, Systems medicine: evolution of systems biology from bench to bedside. Wiley Interdiscip Rev Syst Biol Med, 2015.***7**(4): p. 141-61.

Systems biology

Methodology developed to understand how biological functions arise from multiple and complex interactions among many molecules and cells [1]. Network data are typically obtained with high-throughput data from whole-tissue [2], and single-cell omics [3], co-expression analysis [4], and protein-to-protein identification with two-hybrid assays [5]. Statistical tools include a plethora of mathematical analysis and computerized modeling, ranging from data‐driven methods that aim to identify ‘patterns’, ‘clusters’, ‘correlations’, and ‘topology’, from experimental data [6] (e.g., principal component decomposition methods, supervised classification, linear/nonlinear regression methods, graph analysis, Bayesian networks, persistent homology), to model‐driven methods that aim, instead, to reconstruct networks that can be used in simulations (e.g., machine-learning classifiers, time series analysis, deterministic and stochastic differential equations) (reviewed in [7]).

*McGillivray, P., Network Analysis as a Grand Unifier in Biomedical Data Science. Annual Review of Biomedical Data Science, 2018.***1**.*Pardo, L., et al., Targeted activation of CREB in reactive astrocytes is neuroprotective in focal acute cortical injury. Glia, 2016.***64**(5): p. 853-74.*Pardo, L., et al., CREB Regulates Distinct Adaptive Transcriptional Programs in Astrocytes and Neurons. Sci Rep, 2017.***7**(1): p. 6390.*Zhang, B. and S. Horvath, A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol, 2005.***4**: p. Article17.*Aloy, P. and R.B. Russell, Interrogating protein interaction networks through structural biology. Proceedings of the National Academy of Sciences of the United States of America, 2002.***99**(9): p. 5896-5901.*Bielza, C., Larrañaga, P. , Data-Driven Computational Neuroscience. 2020: Cambridge University Press.**Wang, R.S., B.A. Maron, and J. Loscalzo, Systems medicine: evolution of systems biology from bench to bedside. Wiley Interdiscip Rev Syst Biol Med, 2015.***7**(4): p. 141-61.