@article{discovery10106800,
          volume = {8},
            note = {Copyright {\copyright} 2020 Gorochowski, Hauert, Kreft, Marucci, Stillman, Tang, Bandiera, Bartoli, Dixon, Fedorec, Fellermann, Fletcher, Foster, Giuggioli, Matyjaszkiewicz, McCormick, Montes Olivas, Naylor, Rubio Denniss and Ward. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)(http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.},
           title = {Toward Engineering Biosystems With Emergent Collective Functions},
            year = {2020},
         journal = {Frontiers in Bioengineering and Biotechnology},
        keywords = {synthetic biology, multi-agent modeling, systems biology, emergence, multi-scale, bioengineering, consortia, collectives},
             url = {https://doi.org/10.3389/fbioe.2020.00705},
          author = {Gorochowski, TE and Hauert, S and Kreft, J-U and Marucci, L and Stillman, NR and Tang, T-YD and Bandiera, L and Bartoli, V and Dixon, DOR and Fedorec, AJH and Fellermann, H and Fletcher, AG and Foster, T and Giuggioli, L and Matyjaszkiewicz, A and McCormick, S and Montes Olivas, S and Naylor, J and Rubio Denniss, A and Ward, D},
        abstract = {Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales.}
}