Division of Biomedical Informatics, University of Arkansas for Medical Sciences, COPH/UAMS, Room 3234, 4301W Markham, Slot 781, Little Rock, AR 72205-7199, USA.
Neuroinformatics. 2010 Oct;8(3):201-5. doi: 10.1007/s12021-010-9081-y.
Understanding relationships between the sequence and timing of brain developmental events across a given set of mammalian species can provide information about both neural development and evolution. Yet neurodevelopmental event timing data available from the published literature are incomplete, particularly for humans. Experimental documentation of unknown event timings requires considerable effort that can be expensive, time consuming, and for humans, often impossible. Application of suitable statistical models for translating neurodevelopmental event timings across mammalian species is essential. The present study implements an established statistical model and related functions as an open-source R package (ttime, translating time). The model incorporated into ttime allows predictions of unknown neurodevelopmental timings and explorations of phylogenetic relationships. The open-source package will enable transparency and reproducibility while minimizing redundancy. Sustainability and widespread dissemination will be guaranteed by the active CRAN (Comprehensive R Archive Network) community. The package updates the web-service (Clancy et al. 2007b) www.translatingtime.net by permitting predictions based on curated event timing databases which may include species not yet incorporated in the current model. The R package can be integrated into complex workflows that use the event predictions in their analyses. The package ttime is publicly available and can be downloaded from http://cran.r-project.org/web/packages/ttime/index.html .
理解给定的哺乳动物物种中大脑发育事件的序列和时间之间的关系,可以提供有关神经发育和进化的信息。然而,来自已发表文献的神经发育事件时间数据并不完整,特别是对于人类而言。未知事件时间的实验记录需要大量的工作,这可能既昂贵又耗时,而且对于人类来说,通常是不可能的。将神经发育事件时间跨哺乳动物物种进行翻译的合适统计模型的应用至关重要。本研究实现了一个已建立的统计模型和相关函数作为开源 R 包(ttime,时间翻译)。整合到 ttime 中的模型允许对未知神经发育时间进行预测,并探索系统发育关系。开源软件包将通过最小化冗余来确保透明度和可重复性。可持续性和广泛传播将通过活跃的 CRAN(综合 R 存档网络)社区得到保证。该软件包通过允许基于经过整理的事件时间数据库进行预测来更新网络服务(Clancy 等人,2007b)www.translatingtime.net,这些数据库可能包含当前模型中尚未包含的物种。R 包可以集成到使用事件预测进行分析的复杂工作流程中。ttime 软件包可公开获取,并可从以下网址下载:http://cran.r-project.org/web/packages/ttime/index.html。