Mat2dcorr - A Matlab Toolbox for 2D-COS: Difference between revisions
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== Introduction == | == Introduction == | ||
[[File:2D-COS.jpg|450px|thumb|Mat2dcorr: Screenshot of the 2D control window (left) and the window '2D correlation | [[File:2D-COS.jpg|450px|thumb|Mat2dcorr: Screenshot of the 2D control window (left) and the window ''2D correlation | ||
analysis ... ' (right)]] | analysis ...'' (right)]] | ||
Two-dimensional correlation spectroscopy (2D-COS), sometimes referred to as two-dimensional correlation analysis, has become an invaluable analytical tool for spectroscopic characterization in various fields of application, including protein science, pharmaceutics, biomedical applications, and polymer or nanomaterial research, since its early introduction in 1989. The technique of 2D-COS analysis was originally developed to study dynamic processes in which a spectroscopic probe is used to monitor the effect of an external perturbation on a given system. The system responds to the perturbation by characteristic changes that are monitored spectroscopically, e.g. by continuous acquisition of a spectral time series. The main purpose of 2D-COS investigations is to explore correlations that may exist between perturbation-induced spectral responses. In some situations, the 2D-COS analysis technique is useful not only to detect and visualize such correlations, but also to decipher the sequence of these spectral changes. Sources of perturbation can include changes in temperature, pH, pressure, concentration, or spatial coordinates when examining spatially heterogeneous samples. The 2D correlation concept has proven to be extremely useful in a wide variety of molecular spectroscopy applications based on IR, NIR, Raman, NMR, fluorescence and UV-visible spectroscopy. | Two-dimensional correlation spectroscopy (2D-COS), sometimes referred to as two-dimensional correlation analysis, has become an invaluable analytical tool for spectroscopic characterization in various fields of application, including protein science, pharmaceutics, biomedical applications, and polymer or nanomaterial research, since its early introduction in 1989. The technique of 2D-COS analysis was originally developed to study dynamic processes in which a spectroscopic probe is used to monitor the effect of an external perturbation on a given system. The system responds to the perturbation by characteristic changes that are monitored spectroscopically, e.g. by continuous acquisition of a spectral time series. The main purpose of 2D-COS investigations is to explore correlations that may exist between perturbation-induced spectral responses. In some situations, the 2D-COS analysis technique is useful not only to detect and visualize such correlations, but also to decipher the sequence of these spectral changes. Sources of perturbation can include changes in temperature, pH, pressure, concentration, or spatial coordinates when examining spatially heterogeneous samples. The 2D correlation concept has proven to be extremely useful in a wide variety of molecular spectroscopy applications based on IR, NIR, Raman, NMR, fluorescence and UV-visible spectroscopy. |
Revision as of 17:24, 2 April 2023
mat2dcorr - a free toolbox for performing two-dimensionsonal correlation (2D-COS) analysis with Matlab.
Introduction
Two-dimensional correlation spectroscopy (2D-COS), sometimes referred to as two-dimensional correlation analysis, has become an invaluable analytical tool for spectroscopic characterization in various fields of application, including protein science, pharmaceutics, biomedical applications, and polymer or nanomaterial research, since its early introduction in 1989. The technique of 2D-COS analysis was originally developed to study dynamic processes in which a spectroscopic probe is used to monitor the effect of an external perturbation on a given system. The system responds to the perturbation by characteristic changes that are monitored spectroscopically, e.g. by continuous acquisition of a spectral time series. The main purpose of 2D-COS investigations is to explore correlations that may exist between perturbation-induced spectral responses. In some situations, the 2D-COS analysis technique is useful not only to detect and visualize such correlations, but also to decipher the sequence of these spectral changes. Sources of perturbation can include changes in temperature, pH, pressure, concentration, or spatial coordinates when examining spatially heterogeneous samples. The 2D correlation concept has proven to be extremely useful in a wide variety of molecular spectroscopy applications based on IR, NIR, Raman, NMR, fluorescence and UV-visible spectroscopy.
An introduction into the history, mathematics and basic principles of 2D-COS can be found here: https://en.wikipedia.org/wiki/Two-dimensional_correlation_analysis
Getting Started
- Specification of computer configuration
- Screenshot of the mat2dcorr gui
- Downloading mat2dcorr - How to obtain the mat2dcorr toolbox?
- Installation of the mat2dcorr toolbox
- Disclaimer and license conditions
- Acknowledgement, relevant publications
- Frequently asked questions (FAQ)
Data Import & File Formats
- Import data in the CytoSpec imaging format (CytoSpec/Matlab)
- Import data in the trace format (Matlab)
- Import data in the MS Excel data format
- Format of a 2D-COS result file (Matlab)
Options of the mat2dcorr Toolbox
Related Publications and Web Links
- Two-dimensional correlation analysis (Wikipedia)
- I. Noda. Two-Dimensional Infrared (2D IR) Spectroscopy: Theory and Applications, 1990 Appl. Spectrosc. 44(4): 550-561
- I. Noda. Generalized Two- Dimensional Correlation Method Applicable to Infrared, Raman, and other Types of Spectroscopy, 1993 Appl. Spectrosc. 47(9): 1329-1336
- I. Noda. Determination of Two-Dimensional Correlation Spectra Using the Hilbert Transform, 2000 Appl. Spectrosc. 54(7): 994-999
- P. Lasch & I. Noda. Two-Dimensional Correlation Spectroscopy for Multimodal Analysis of FT-IR, Raman, and MALDI-TOF MS Hyperspectral Images with Hamster Brain Tissue. Anal. Chem. 2017, 89, 9, 5008–5016
- P. Lasch & I. Noda. Two-Dimensional Correlation Spectroscopy (2D-COS) for Analysis of Spatially Resolved Vibrational Spectra. 2019 Appl. Spectrosc. 73(4): 359-379
Apr 02, 2023: more details of the mat2dcorr Matlab toolbox will follow soon