Treffer: Preprocessing and Analyzing Raman Spectra Using Python †.

The inherent complexity of the Raman spectra of biomedical samples reflects the intricate molecular composition and intermolecular interactions of these diverse systems. Unraveling the complexities of biological Raman spectra is essential for bioscience and bioengineering research because it provides insight into cellular processes, disease states, and drug interactions. For the effective analysis of such complex data, robust and cutting-edge software is required that provides sophisticated algorithms for data preprocessing, thereby enhancing the signal-to-noise ratio and revealing hidden spectral information. In addition, novel applications of this type may include machine learning algorithms for automated clustering analysis, enabling the identification of biomolecules and their conformational changes in diverse biological specimens. We present a Python 3 package built around popular scientific Python libraries that aims to provide Raman spectroscopists with user-friendly programming tools for the analysis of complex biomedical Raman data. [ABSTRACT FROM AUTHOR]

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