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Updated: Sep 15, 2025

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A Practical Guide to Phylogenetics for Nonexperts
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贝叶斯推断的健身景观通过树结构分支过程的贝叶斯推断
Xiang Ge Luo1,2, Jack Kuipers1,2, Kevin Rupp1,2
1Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.
Bioinformatics (Oxford, England)
|July 15, 2025
概括
FiTree通过分析单细胞测序数据的突变树来模拟瘤进化. 这种方法准确地推断出健身景观和表观效应,改善了我们对癌症进展的理解.
科学领域:
- 计算生物学 计算生物学
- 进化生物学 进化生物学
- 癌症基因组学 癌症基因组学
背景情况:
- 瘤进化是复杂的,由突变和选择驱动,导致分子异质性.
- 单细胞测序数据允许重建瘤进化史作为突变树.
- 现有的模型往往无法整合突变,选择和进化史.
研究的目的:
- 开发一种新的模型,从单细胞瘤突变树推断出癌症健身景观.
- 为了解决癌症进展中的表位健康效应和进化史.
主要方法:
- 介绍了FiTree,一个树结构的多类型分支过程模型.
- 整合了表皮性适应性参数化和贝叶斯推理方案.
- 使用单细胞瘤突变树作为输入.
主要成果:
- 在推断健身景观方面,FiTree的性能优于最先进的方法.
- 在急性髓性白血病数据集中确定了表皮性健康影响.
- 预测未来突变事件的量化不确定性.
结论:
- FiTree为癌症进展建模和人口遗传学提供了一个统一的框架.
- 该模型提供了对瘤演变的洞察力,并可以为治疗策略提供信息.
- 作为一个具有分析工作流程的Python包,FiTree是可用的.
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