Disclaimer and License Conditions and Mat2dcorr - A Matlab Toolbox for 2D-COS: Difference between pages

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You are using the mat2dcorr toolbox at your own risk! There is no responsibility for damages, problems etc. resulting from use of this code. Furthermore, there is also no warranty for bug-free operation, fitness for a particular purpose or the appropriate behavior of the program. Please report software bugs, inconsistencies or suggestions for new functions to ''lasch at peter-lasch.de''.
__FORCETOC__
mat2dcorr - a free toolbox for performing two-dimensionsonal correlation (2D-COS) analysis with [https://www.mathworks.com Matlab].<br>


The software is distributed under the CC BY-NC-SA 4.0 license (Creative Commons Attribution-NonCommercial-ShareAlike)
== Introduction ==
 
All trademarks mentioned are property of their owners.
[[File:2D-COS.jpg|450px|thumb|Mat2Dcorr: Screenshot of the 2D control window (left) and the window '2D correlation
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.
 
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 ==
* [[Computer_Specification|Specification of computer configuration]]
* [[Screenshot_of_mat2dcorr|Screenshot of the mat2dcorr gui]]
* <span style="color:red"> Downloading mat2dcorr</span> - [[How_to_obtain_the_mat2dcorr_toolbox|How to obtain the mat2dcorr toolbox?]]
* [[Installation_of_the_mat2dcorr_toolbox|Installation of the mat2dcorr toolbox]]
* [[Disclaimer_and_License_Conditions |Disclaimer and license conditions]]
* [[mat2dcorr_-_Relevant Publications|Acknowledgement, relevant publications]]
* [[Frequently_Asked_Questions_(FAQ)|Frequently asked questions (FAQ)]]
 
== Data Import & File Formats  ==
 
* [[Matlab_Imaging_Format|Import data in the imaging format (Matlab)]]
* [[Matlab_Trace_Format|Import data in the trace format (Matlab)]]
* [[Format_of_a_2D-COS_Result_File|Format of a 2D-COS result file (Matlab)]]
 
== Options of the mat2dcorr Toolbox ==
 
* [[Options_of_the_2D-COS_Main_Figure| Options of the 2D-COS main figure]]
* [[Options_of_the_2D-COS_Control_Window| Options of the 2D-COS control window]]
 
== Related Publications and Web Links ==
 
[[File:GraphAbstr.gif|500px|thumb|Mat2Dcorr: Illustration of Heterspectral 2D-COS (FTIR vs. Raman)]]
 
* [https://en.wikipedia.org/wiki/Two-dimensional_correlation_analysis Two-dimensional correlation analysis] (Wikipedia)
 
* I. Noda. [https://doi.org/10.1366/0003702904087398 Two-Dimensional Infrared (2D IR) Spectroscopy: Theory and Applications], 1990 Appl. Spectrosc. 44(4): 550-561
 
* I. Noda. [https://doi.org/10.1366/0003702934067694 Generalized Two- Dimensional Correlation Method Applicable to Infrared, Raman, and other Types of Spectroscopy], 1993 Appl. Spectrosc. 47(9): 1329-1336
 
* I. Noda. [https://doi.org/10.1366/0003702001950472 Determination of Two-Dimensional Correlation Spectra Using the Hilbert Transform], 2000 Appl. Spectrosc. 54(7): 994-999
 
* P. Lasch & I. Noda. [https://doi.org/10.1021/acs.analchem.7b00332 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. [https://doi.org/10.1177/0003702818819880 Two-Dimensional Correlation Spectroscopy (2D-COS) for Analysis of Spatially Resolved Vibrational Spectra]. 2019 Appl. Spectrosc. 73(4): 359-379
 
<br> &nbsp; <br>
 
Mar 18, 2023: more details of the mat2Dcorr Matlab toolbox will follow soon

Revision as of 16:19, 2 April 2023

mat2dcorr - a free toolbox for performing two-dimensionsonal correlation (2D-COS) analysis with Matlab.

Introduction

Mat2Dcorr: Screenshot of the 2D control window (left) and the window '2D correlation 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.

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

Data Import & File Formats

Options of the mat2dcorr Toolbox

Related Publications and Web Links

Mat2Dcorr: Illustration of Heterspectral 2D-COS (FTIR vs. Raman)


 

Mar 18, 2023: more details of the mat2Dcorr Matlab toolbox will follow soon

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