I-BioStat, Hasselt University, Diepenbeek, Belgium.
J Am Soc Mass Spectrom. 2012 Apr;23(4):753-63. doi: 10.1007/s13361-011-0326-2. Epub 2012 Feb 15.
In this article, we present a computation- and memory-efficient method to calculate the probabilities of occurrence and exact center-masses of the aggregated isotopic distribution of a molecule. The method uses fundamental mathematical properties of polynomials given by the Newton-Girard theorem and Viete's formulae. The calculation is based on the atomic composition of the molecule and the natural abundances of the elemental isotopes in normal terrestrial matter. To evaluate the performance of the proposed method, which we named BRAIN, we compare it with the results obtained from five existing software packages (IsoPro, Mercury, Emass, NeutronCluster, and IsoDalton) for 10 biomolecules. Additionally, we compare the computed mass centers with the results obtained by calculating, and subsequently aggregating, the fine isotopic distribution for two of the exemplary biomolecules. The algorithm will be made available as a Bioconductor package in R, and is also available upon request.
在本文中，我们提出了一种计算分子聚合同位素分布出现概率和精确质心的计算效率和存储效率方法。该方法利用了牛顿-吉拉德定理和维特公式给出的多项式的基本数学性质。计算基于分子的原子组成和正常地球物质中元素同位素的天然丰度。为了评估我们命名为 BRAIN 的方法的性能，我们将其与五个现有软件包（IsoPro、Mercury、Emass、NeutronCluster 和 IsoDalton）针对 10 种生物分子的结果进行了比较。此外，我们还将计算出的质心与通过计算随后聚合两个示例生物分子的精细同位素分布得到的结果进行了比较。该算法将作为 R 中的 Bioconductor 包提供，也可以根据要求提供。
