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. 2018 Feb 24;4:11. doi: 10.1038/s41540-018-0047-2

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — Selection of the most informative iPSC-CM simulation protocols for regression model optimization. a, b Histograms indicating how APD₉₀ (a) and CaTA (b) vary across a heterogeneous population of iPSC-CMs under different simulated experimental conditions. The black, shaded histogram, representing population behavior with baseline spontaneous contraction is compared with alternative experimental conditions such as 0.5 Hz electrical stimulation (0.5 Hz, orange), 2 Hz electrical stimulation (2.0 Hz, green), and increased (300 mM) extracellular [Na⁺] ([Na⁺]_o high, purple). c, d Averaged R² values across all predicted features with five-fold cross-validation, with different numbers of experimental conditions for sequential inclusion (c) and sequential exclusion (d) methods. These procedures identified the three most informative protocols (3-MOST, purple dash square, left) and the three least informative protocols (3-LEAST, orange dash square, right). e, f Distributions of adjusted R² values for APD₉₀ (e) and CaTA (f) of the 56 regression models that can be built by randomly choosing three protocols from the initial set of eight. Regression models that select two or more protocols from the 3-MOST list (purple) exhibit better predictive power than models that select two or more protocols from the 3-LEAST list (orange)