PyLDM - An open source package for lifetime density analysis of time-resolved spectroscopic data.
PyLDM - An open source package for lifetime density analysis of time-resolved spectroscopic data.
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DOI：
10.1371/journal.pcbi.1005528
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发表时间：
2017-05
影响因子：
4.3
通讯作者：
van Thor JJ
中科院分区：
文献类型：
--
作者：
Dorlhiac GF;Fare C;van Thor JJ
超快光谱学为飞秒和皮秒范围内的探测过程提供了时间分辨率。这使得许多光活性化合物和配合物的能量和电荷转移的调查。然而，对所得数据的分析可能是复杂的，特别是在更复杂的生物系统中，例如光系统。从历史上看，全球分析和目标建模的双重方法已被用来阐明动力学描述的系统，并分别瞬时物种的身份。对于前者，寿命密度分析（LDA）技术提供了一个有吸引力的选择。虽然全局分析将数据近似为少量指数衰减的总和，通常在2-4的数量级，但LDA使用100个寿命的半连续分布。这允许阐明的寿命分布，这可能是预期从调查的复杂系统与许多发色团，而不是平均值。此外，在全局分析中衰减的线性组合的固有假设意味着该技术无法描述动态运动，这是一个可以用LDA解决的过程。这项技术是十多年前由Holzwarth小组引入光合作用领域的。该分析已被证明是一个重要的工具，以评估复杂的动态，如光合能量转移，并补充传统的全球和目标分析技术。虽然理论已经得到了很好的描述，但到目前为止还没有开源代码可用于执行寿命密度分析。因此，我们引入了一个基于python（2.7）的包PyLDM来满足这一需求。此外，我们提供了一个直接比较的LDA与更熟悉的全球分析的能力，以及提供了一些统计技术，用于处理噪声数据的正则化。
Ultrafast spectroscopy offers temporal resolution for probing processes in the femto- and picosecond regimes. This has allowed for investigation of energy and charge transfer in numerous photoactive compounds and complexes. However, analysis of the resultant data can be complicated, particularly in more complex biological systems, such as photosystems. Historically, the dual approach of global analysis and target modelling has been used to elucidate kinetic descriptions of the system, and the identity of transient species respectively. With regards to the former, the technique of lifetime density analysis (LDA) offers an appealing alternative. While global analysis approximates the data to the sum of a small number of exponential decays, typically on the order of 2-4, LDA uses a semi-continuous distribution of 100 lifetimes. This allows for the elucidation of lifetime distributions, which may be expected from investigation of complex systems with many chromophores, as opposed to averages. Furthermore, the inherent assumption of linear combinations of decays in global analysis means the technique is unable to describe dynamic motion, a process which is resolvable with LDA. The technique was introduced to the field of photosynthesis over a decade ago by the Holzwarth group. The analysis has been demonstrated to be an important tool to evaluate complex dynamics such as photosynthetic energy transfer, and complements traditional global and target analysis techniques. Although theory has been well described, no open source code has so far been available to perform lifetime density analysis. Therefore, we introduce a python (2.7) based package, PyLDM, to address this need. We furthermore provide a direct comparison of the capabilities of LDA with those of the more familiar global analysis, as well as providing a number of statistical techniques for dealing with the regularization of noisy data.