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Taming the BEAST—A Community Teaching Material Resource for BEAST 2

机译:驯服野兽的社区教学资源2

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Phylogenetics and phylodynamics are central topics in modern evolutionary biology. Phylogenetic methods reconstruct the evolutionary relationships among organisms, whereas phylodynamic approaches reveal the underlying diversification processes that lead to the observed relationships. These two fields have many practical applications in disciplines as diverse as epidemiology, developmental biology, palaeontology, ecology, and linguistics. The combination of increasingly large genetic data sets and increases in computing power is facilitating the development of more sophisticated phylogenetic and phylodynamic methods. Big data sets allow us to answer complex questions. However, since the required analyses are highly specific to the particular data set and question, a black-box method is not sufficient anymore. Instead, biologists are required to be actively involved with modeling decisions during data analysis. The modular design of the Bayesian phylogenetic software package BEAST 2 enables, and in fact enforces, this involvement. At the same time, the modular design enables computational biology groups to develop new methods at a rapid rate. A thorough understanding of the models and algorithms used by inference software is a critical prerequisite for successful hypothesis formulation and assessment. In particular, there is a need for more readily available resources aimed at helping interested scientists equip themselves with the skills to confidently use cutting-edge phylogenetic analysis software. These resources will also benefit researchers who do not have access to similar courses or training at their home institutions. Here, we introduce the “Taming the Beast” (https://taming-the-beast.github.io/) resource, which was developed as part of a workshop series bearing the same name, to facilitate the usage of the Bayesian phylogenetic software package BEAST 2.
机译:系统发育和文学学称为现代进化生物学中的中心主题。系统发育方法重建生物体中的进化关系,而文学方法揭示了导致观察到的关系的潜在多样化过程。这两个领域在学科中具有许多实际应用,与流行病学,发育生物学,古生物学,生态学和语言学一样多样化。越来越大的遗传数据集的组合和计算能力的增加是促进更复杂的系统发育和文学发育和文学方法的发展。大数据集允许我们回答复杂的问题。但是,由于所需的分析对特定数据集和问题非常特定,因此不再具有黑盒方法。相反,生物学家必须在数据分析期间积极参与建模决策。贝叶斯系统发育软件包野兽2的模块化设计使能实现这一参与。与此同时,模块化设计使计算生物学组能够以快速的速率开发新方法。彻底了解推理软件使用的模型和算法是成功假设配方和评估的关键先决条件。特别是,需要更容易获得更多的资源,旨在帮助感兴趣的科学家用自信地使用尖端系统发育分析软件的技能。这些资源也将受益于无法获得类似课程或其家庭机构培训的研究人员。在这里,我们介绍了“驯服野兽”(https://taming-the-beast.github.io/)资源,该资源是载有同名的车间系列的一部分,以促进贝叶斯系统发育的使用软件包野兽2。

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