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spectral-analysis

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Preliminary investigation of machine learning techniques to perform parameters estimation for different crystal structure: hexagonal, monoclinic, orthorhombic, tetragonal, triclinic, trigonal.

  • Updated Apr 25, 2023
  • Jupyter Notebook

This project focuses on improving the analysis and separation of overlapping spectral peaks in mass spectrometry data. Accurate detection and separation of these peaks are crucial for identifying substances in complex mixtures, which has applications in various fields such as biochemistry, pharmacology, and environmental science.

  • Updated Jun 25, 2024
  • Jupyter Notebook

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