Department of Chemistry, Sharif University of Technology, Tehran, Iran.
Department of Environmental Chemistry, IDAEA-CSIC, 08034, Barcelona, Spain.
Angew Chem Int Ed Engl. 2022 Nov 2;61(44):e201801134. doi: 10.1002/anie.201801134. Epub 2022 Sep 29.
This Review summarizes how big (bio)chemical data (BBCD) can be analyzed with multivariate chemometric methods and highlights some of the important challenges faced by modern analytical researches. Here, the potential of chemometric methods to solve BBCD problems that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements will be discussed, with an emphasis on their applications to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this Review, the importance of "big data" and of their relevance to (bio)chemistry are first discussed. Thereafter, analytical tools which can produce BBCD are presented as well as the theoretical background of chemometric methods and their limitations when they are applied to BBCD. Finally, the importance of chemometric methods for the analysis of BBCD in different chemical disciplines is highlighted with some examples. In this work, we have tried to cover many of the current applications of big data analysis in the (bio)chemistry field.
本综述总结了如何使用多元化学计量学方法分析大（生物）化学数据（BBCD），并强调了现代分析研究所面临的一些重要挑战。在这里，将讨论化学计量学方法在解决色谱、光谱和高光谱成像测量中遇到的 BBCD 问题方面的潜力，重点是它们在组学科学中的应用。此外，还就如何解决 BBCD 分析提供了一些见解和观点，并讨论了获得更可靠定性和定量结果所需的程序。在本综述中，首先讨论了“大数据”的重要性及其与（生物）化学的相关性。此后，还介绍了可以产生 BBCD 的分析工具，以及化学计量学方法的理论背景及其在应用于 BBCD 时的局限性。最后，强调了化学计量学方法在不同化学学科中分析 BBCD 的重要性，并提供了一些示例。在这项工作中，我们试图涵盖大数据分析在（生物）化学领域的许多当前应用。
