Event Abstract Back to Event A combinatorial approach for mapping the interactions of multiple inputs to a biological system in a tractable number of experiments Vladimir Brezina1* and Brian Fulton-Howard1 1 Icahn School of Medicine at Mount Sinai, Department of Neuroscience, United States Multiple simultaneous inputs (e.g., neurochemical agents, drugs, therapeutic interventions) act together to affect the output of complex biological systems such as neurons and neural circuits or organs such as the heart. Describing how all these inputs act together on a system is difficult because the inputs often interact in ways that cannot be predicted from their individual actions. This happens because biological systems are nonlinearly coupled networks of many components through which the presence of one input can change the effect of another on the output. Full experimental mapping of all interactions between inputs is currently impractical for nontrivial input sets because of the combinatorial explosion: there are simply too many combinations of inputs to test each combination individually. To solve the problem, we have developed a block-design approach in which we construct a small number of test sets, each containing a number of pairs (or higher tuples) of the inputs, such that together all the test sets contain all possible pairs multiple times. Similar algorithms are used in communications and computer systems testing, but our algorithm must satisfy the additional need for repeated testing to deal with inter-preparation variability seen in biological systems. Our algorithm furthermore adaptively reduces the number of experiments required depending on the results obtained so far. Finally, it incorporates statistical tests to evaluate how nonlinearly “unexpected” each pairwise interaction is, relative to the prediction from the linear combination of effects of the two (or more) inputs alone. The statistic ranks all of the pairwise interactions from the most to the least unexpected. The algorithm thus functions as a global screen for the most unexpected interactions in the input set. Even large numbers of inputs require only small, experimentally tractable, numbers of test sets. Altogether, our approach promises to be able to guide the experimental discovery and global mapping of interactions between inputs to a system without any knowledge of the internal structure of the system. We are testing and further refining the approach using the Luo-Rudy computational model of mammalian ventricular myocytes, and then applying it experimentally to map the interactions between the many neuromodulators of a crustacean cardiac system. Acknowledgements Funded by NSF IOS 1146019 Keywords: neuromodulators, drugs, Multiple inputs, Combinatorial explosion, Block design, Computational Biology, biological networks Conference: Neuroinformatics 2015, Cairns, Australia, 20 Aug - 22 Aug, 2015. Presentation Type: Poster, to be considered for oral presentation Topic: Computational neuroscience Citation: Brezina V and Fulton-Howard B (2015). A combinatorial approach for mapping the interactions of multiple inputs to a biological system in a tractable number of experiments. Front. Neurosci. Conference Abstract: Neuroinformatics 2015. doi: 10.3389/conf.fnins.2015.91.00051 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 07 Apr 2015; Published Online: 05 Aug 2015. * Correspondence: Dr. Vladimir Brezina, Icahn School of Medicine at Mount Sinai, Department of Neuroscience, New York, NY, United States, vladimir.brezina@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Vladimir Brezina Brian Fulton-Howard Google Vladimir Brezina Brian Fulton-Howard Google Scholar Vladimir Brezina Brian Fulton-Howard PubMed Vladimir Brezina Brian Fulton-Howard Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.