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. 2024 Oct 30;25:340. doi: 10.1186/s12859-024-05968-3

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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Fig. 6 — Key features in the combined ECFP4, Sequence, and IFP model based on SHAP values. This plot displays the top 20 most influential features in the combined model, ranked by their mean absolute SHAP values. Each dot represents an instance in the test set, positioned on the X-axis by its SHAP value. ECFP4 bits are color-coded: red for "On" (value = 1) and blue for "Off" (value = 0). Sequence values are indicated by a gradient color scale, with blue for lower values and red for higher values.