Visualization methods and support vector machines as tools for determining markers in models of heterogeneous populations: Proapoptotic signaling as a case study
Visualization methods and support vector machines as tools for determining markers in models of heterogeneous populations: Proapoptotic signaling as a case study
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可视化方法和支持向量机作为确定异质群体模型中标记的工具：促凋亡信号传导作为案例研究
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发表时间：
2011
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通讯作者：
D. Weiskopf
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作者：
J. Hasenauer;Julian Heinrich;M. Doszczak;P. Scheurich;D. Weiskopf
动力。可视化方法和支持向量机作为确定异质群体模型中标记物的工具：促凋亡信号传导作为案例研究。在Proc. of 8 th Workshop for Computational Systems Biology（WCSB 2011），苏黎世，瑞士，第61-64页，2011年。摘要近年来，细胞群体模型已经变得非常普遍，因为它们允许研究群体异质性。不幸的是，到目前为止，群体模型的复杂性阻碍了允许深入研究异质性来源的分析工具的发展，如遗传学和表观遗传学。在本文中，我们提出了一个探索性的分析相结合的平行坐标图和非线性支持向量机，以确定在异质细胞群体的决策过程中的细胞到细胞的变异性的主要来源。该方法被应用于分析癌细胞群中的促凋亡信号转导，并确定决策标志物。
ower. Visualization methods and support vector machines as tools for determining markers in models of heterogeneous populations: Proapoptotic signaling as a case study. In Proc. of 8th Workshop for Computational Systems Biology (WCSB 2011), Zurich, Switzerland, pages 61-64, 2011. Abstract In recent years, cell population models have become very common, as they allow for the study of population heterogeneity. Unfortunately, the complexity of population models so far has prevented the devel- opment of analysis tools permitting an in-depth study of the source of heterogeneity, like genetics and epi- genetics. In this paper we propose an explorative analysis combining parallel-coordinate plots and nonlinear support vector machines to determine the main sources of cell-to-cell variability within decision processes in heterogeneous cell populations. The approach is applied to analyze proapoptotic signal transduction in cancer cell populations and to determine decision markers.