Model training of generalized Lotka–Volterra (gLV) to time‐resolved measurements of monospecies and pairwise assemblages Model training of generalized.

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Model training of generalized Lotka–Volterra (gLV) to time‐resolved measurements of monospecies and pairwise assemblages Model training of generalized Lotka–Volterra (gLV) to time‐resolved measurements of monospecies and pairwise assemblages Species relative abundance as a function of time for all pairwise communities. Experimental measurements and model fits based on T3 are represented as data points and lines, respectively. In each subplot, time and species relative abundance are displayed on the x‐ and y‐axis, respectively. Stars denote datasets with a sum of mean squared errors greater than 0.15. Error bars represent 1 s.d. from the mean of at least three biological replicates.Temporal changes in species relative abundance of a selected set of pairwise assemblages inoculated at 5% species A, 95% species B or 95% species A, 5% species B based on OD600 values. Time and relative abundance are represented on the x‐ and y‐axis, respectively. Data points and lines represent experimental measurements and model fits to T3, respectively. Error bars represent 1 s.d. from the mean of at least three biological replicates. Stars denote datasets with a sum of mean squared errors greater than 0.15.Inferred inter‐species interaction coefficients for the gLV model trained on T3. Gray and green edges denote negative (αij < 0) and positive (αij > 0) interaction coefficients. The edge width and node size represent the magnitude of the inter‐species interaction coefficient and steady state monospecies abundance (xe = −μiαii−1), respectively. To highlight significant interactions, inter‐species interaction coefficients with a magnitude less than 1e‐5 were not displayed. Ophelia S Venturelli et al. Mol Syst Biol 2018;14:e8157 © as stated in the article, figure or figure legend