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Network interactions optimize some intrinsic cost functions that are unknown and involve for example energy efficiency, robustness, resilience, and frailty. A wide range of networks exist in biology, from gene regulatory networks important for organismal development, protein interaction networks that govern physiology and metabolism, and neural networks that store and convey information to networks of microbes that form microbiomes within hosts, animal contact networks that underlie social systems, and networks of populations on the landscape connected by migration. Increasing availability of extensive (big) data is amplifying our ability to quantify biological networks. Similarly, theoretical methods that describe network structure and dynamics are being developed. Beyond static networks representing snapshots of biological systems, collections of longitudinal data series can help either at defining and characterizing network dynamics over time or analyzing the dynamics constrained to networked architectures. Moreover, due to interactions with the environment and other biological systems, a biological network may not be fully observable. Also, subnetworks may emerge and disappear as a result of the need for the biological system to cope with for example invaders or new information flows. The confluence of these developments renders tractable the question of how the structure of biological networks predicts and controls network dynamics. In particular, there may be structural features that result in homeostatic networks with specific higher-order statistics (e.g., multifractal spectrum), which maintain stability over time through robustness and\/or resilience to perturbation. Alternative, plastic networks may respond to perturbation by (adaptive to catastrophic) shifts in structure. Here, we explore the opportunity for discovering universal laws connecting the structure of biological networks with their function, positioning them on the spectrum of time-evolving network structure, that is, dynamics of networks, from highly stable to exquisitely sensitive to perturbation. If such general laws exist, they could transform our ability to predict the response of biological systems to perturbations\u2014an increasingly urgent priority in the face of anthropogenic changes to the environment that affect life across the gamut of organizational scales.<\/jats:p>","DOI":"10.1093\/icb\/icab069","type":"journal-article","created":{"date-parts":[[2021,5,21]],"date-time":"2021-05-21T07:09:26Z","timestamp":1621580966000},"page":"1991-2010","source":"Crossref","is-referenced-by-count":20,"title":["Biological Networks across Scales\u2014The Theoretical and Empirical Foundations for Time-Varying Complex Networks that Connect Structure and Function across Levels of Biological Organization"],"prefix":"10.1093","volume":"61","author":[{"given":"Paul","family":"Bogdan","sequence":"first","affiliation":[{"name":"Ming-Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, Los Angeles, CA 90007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gustavo","family":"Caetano-Anoll\u00e9s","sequence":"additional","affiliation":[{"name":"Department of Crop Sciences, University of Illinois, Urbana\u2013Champaign, Champaign, IL 61801, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Jolles","sequence":"additional","affiliation":[{"name":"Carlson College of Veterinary Medicine and Department of Integrative Biology, Oregon State University, Corvallis, OR 97331, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyunju","family":"Kim","sequence":"additional","affiliation":[{"name":"The Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85287-0506, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Morris","sequence":"additional","affiliation":[{"name":"Baruch Institute for Marine and Coastal Sciences, University of South Carolina, Columbia, SC 29201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheryl A","family":"Murphy","sequence":"additional","affiliation":[{"name":"Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine","family":"Royer","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward H","family":"Snell","sequence":"additional","affiliation":[{"name":"Hauptman-Woodward Medical Research Institute and SUNY at Buffalo, Buffalo, NY 14203, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam","family":"Steinbrenner","sequence":"additional","affiliation":[{"name":"Department of Biology, University of Washington, 24 Kincaid Hall, Seattle, WA 98105, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Strausfeld","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, University of Arizona, Tucson, AZ 85721, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,5,22]]},"reference":[{"key":"2022052200083007100_icab069-B1","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1038\/nature09182","article-title":"Link communities reveal multiscale complexity in networks","volume":"466","author":"Ahn","year":"2010","journal-title":"Nature"},{"key":"2022052200083007100_icab069-B2","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1093\/toxsci\/kfw018","article-title":"Tipping the balance: hepatotoxicity and the 4 apical key events of hepatic steatosis","volume":"150","author":"Angrish","year":"2016","journal-title":"Toxicol Sci"},{"key":"2022052200083007100_icab069-B3","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1126\/science.1203877","article-title":"Evidence for network evolution in an Arabidopsis interactome map","volume":"333","author":"Arabidopsis Interactome Mapping Consortium","year":"2011","journal-title":"Science"},{"key":"2022052200083007100_icab069-B4","first-page":"593","article-title":"Stress induces biphasic-rewiring and modularization patterns in metabolomics networks of Escherichia coli","volume":"2012","author":"Aziz","year":"2012","journal-title":"IEEE Intl Conf Bioinf Biomed"},{"key":"2022052200083007100_icab069-B5","doi-asserted-by":"crossref","first-page":"25058","DOI":"10.1038\/srep25058","article-title":"The early history and emergence of molecular functions and modular scale-free network behavior","volume":"6","author":"Aziz","year":"2016","journal-title":"Sci Rep"},{"key":"2022052200083007100_icab069-B6","article-title":"Evolution of networks of protein domain organization. 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