We have built an online tool with a user-friendly and browser-based interface to facilitate the processing of high resolution and precision oil mass spectrometry data. DropMS does not require software installations. Mass spectra are sent and processed by the server using various algorithms reported in the literature, such as S/N ratio filters, recalibrations, chemical formula assimilations, and data visualization using graphs and diagrams popularly known in mass spectrometry as Van Krevelen and Kendrick diagrams and DBE vs C#. To validate the algorithms used and the processing results, the same mass spectrum of a typical Brazilian oil sample was analyzed by ESI(+)-FT-ICR/MS and processed using Sierra Analytics DropMS and Composer to obtain good agreement between the heteroatomic classes found and the number of compounds assigned. The MS has chemical information spread over the entire spectrum. The PLS multivariate regression has the main objective of decomposing the most important information into latent variables in order to quantify the most evaluated properties. Finally, 12 processed petroleum FT-ICR MS spectra were used for a partial least-squares regression with seven latent variables for R2 = 0.971 and RMSEC of 0.997 for API density property with a reference value range of 21-42.

中文翻译：

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DropMS：基于Web服务器的石油化学数据处理，用于高分辨率质谱。

我们已经构建了一个在线工具，该工具具有基于用户的友好和基于浏览器的界面，以促进高分辨率和精密油质谱数据的处理。DropMS不需要安装软件。服务器使用文献中报道的各种算法来发送和处理质谱，例如，信噪比过滤器，重新校准，化学式同化以及使用在质谱术中众所周知的Van Krevelen和Kendrick图和DBE与C＃。为了验证所使用的算法和处理结果，通过ESI（+）-FT-ICR / MS分析了典型巴西石油样品的相同质谱，并使用Sierra Analytics DropMS和Composer处理了该质谱，从而获得了所发现的杂原子类之间的良好一致性以及分配的化合物数量。MS的化学信息遍布整个光谱。PLS多元回归的主要目标是将最重要的信息分解为潜在变量，以便量化最评估的属性。最后，使用12个处理过的石油FT-ICR MS光谱进行偏最小二乘回归，其中7个潜在变量的R2 = 0.971，RMSEC为0.997，API密度特性的参考值范围为21-42。