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基于内核的粒子过用于在部分观察到的布尔动态系统中进行可扩展的推理
1Northeastern University, Department of Electrical and Computer Engineering, Boston, MA, USA.
概括
本研究介绍了一种基于核的新型粒子过方法,用于在部分观察到的布尔动态系统 (POBDS) 中有效推断参数. 这种方法提高了复杂的生物和安全网络的可扩展性.
科学领域:
- 系统生物学 系统生物学
- 计算生物学 计算生物学
- 网络安全 网络安全
背景情况:
- 部分观察布尔动态系统 (POBDS) 对于建模基因动态和网络安全非常有效.
- 由于计算成本高,POBDS的现有推断方法面临可扩展性问题.
- 有效的参数推断对于理解复杂的生物和安全系统至关重要.
研究的目的:
- 为部分观察布尔动态系统 (POBDS) 开发一种可扩展的推理方法.
- 为解决POBDS的概率评估和参数空间探索中的计算挑战.
- 使用POBDS提高复杂生物和安全网络建模的效率.
主要方法:
- 建议采用基于内核的颗粒过方法.
- 用高斯过程 (GPs) 高效地近似概率函数.
- 贝叶斯优化用于指导参数搜索,平衡探索和利用.
主要成果:
- 拟议的方法显著提高了POBDS推断的可扩展性.
- 高斯过程有效地代表了不确定的概率评估.
- 贝叶斯优化有效地识别最佳参数,减少计算负担.
结论:
- 基于内核的粒子过方法为POBDS推断提供了一个可扩展的解决方案.
- 这种方法提高了POBDS在系统生物学和网络安全中的应用性.
- 该方法在哺乳动物细胞周期和T细胞白血病网络上成功验证.
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