Excel Trace Format and Mat2dcorr - Relevant Publications: Difference between pages

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With version 1.04 of the mat2dcorr toolbox, besides hyperspectral imaging data in the CytoSpec data format and Matlab trace files, spectra data from MS Excel spreadsheets can now be loaded. MS Excel spreadsheets should contain spectra series in a 2D data format where the spectra must be arranged as columns and the wavenumber vectors as rows. It is also important that the first row contains the vector with the data entries of the perturbing variable (temperature, pressure, etc.). The first column should contain the y-vector (wavenumber, frequencies, Raman shift vector) starting from row no. 2. <br>
Two-dimensional correlation spectroscopy (2D-COS), or two-dimensional correlation analysis is known as a set of mathematical techniques useful to study changes in dynamic spectra. Dynamic spectra are often represented by spectra series obtained from a sample that was subjected to an external perturbation.<br> &nbsp;<br>
The 2D-COS analysis technique has been initially developed by [https://en.wikipedia.org/wiki/Isao_Noda Isao Noda] in the 1980s.  


In order to use own data by means of the MS Excel import function, it is recommended to analyze the structure of the example file ''linescandata.xlsx'' and to replace the spectral data contained therein with own data. <br>
<ul><ul>
{| class="wikitable" width=800
|-
| Wikipedia link to 2D-COS: [https://en.wikipedia.org/wiki/Two-dimensional_correlation_analysis Two-dimensional correlation analysis]
|}
&nbsp; <br>
</ul></ul>
__FORCETOC__
== Relevant Publications ==


Download MS Excel file ''linescandata.xlsx'': [http://www.peter-lasch.de/2dcorr/linescandata.xlsx]<br>
'''Main concepts of two-dimensional correlation analysis'''<br>
Basic principles of generalized 2D correlation spectroscopy are outlined in the following series of scientific publications: <br>
<ul>
<li>Noda, I..<br>
[https://doi.org/10.1366/0003702904087398 Two-Dimensional Infrared (2D IR) Spectroscopy: Theory and Applications],<br>
'''1990''' ''Appl Spectrosc''. 44(4): 550-561.</li>
<li>Noda, I.<br>
[https://doi.org/10.1366/0003702934067694 Generalized Two-Dimensional Correlation Method Applicable to Infrared, Raman, and other Types of Spectroscopy],<br>
'''1993''' ''Appl Spectrosc''. 47(9): 1329-1336.</li>
<li>Noda, I.<br>
[https://doi.org/10.1366/0003702001950472 Determination of Two-Dimensional Correlation Spectra Using the Hilbert Transform],<br>
'''2000''' ''Appl Spectrosc''. 54(7): 994-999.</li>
</ul>


To load MS Excel trace files select Load Data &rarr; Excel data format &rarr; x-data, or y-data from the Load Data menu bar. <br> &nbsp; <br>
&nbsp;<br>


== Related links  ==
== Publications in which the mat2dcorr toolbox has been used or mentioned ==


* [[Matlab_Imaging_Format|Import data in the CytoSpec imaging format (CytoSpec/Matlab)]]
<ol>
* [[Matlab_Trace_Format|Import data in the trace format (Matlab)]]
<li>Lasch, P. and I. Noda '''2017'''<br>
* [[Format_of_a_2D-COS_Result_File|Format of a 2D-COS result file (Matlab)]]
[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].<br>
''Anal Chem''. 89(9): 5008-5016.</li>
 
<li>Lasch, P. and I. Noda '''2019''' <br>
[https://doi.org/10.1177/0003702818819880 Two-Dimensional Correlation Spectroscopy (2D-COS) for Analysis of Spatially Resolved Vibrational Spectra].<br>
''Appl Spectrosc''. 73(4): 359-379.</li>
 
<li>Sun, Y., Wang, X., Xia, S., & Zhao, J. '''2021'''<br>
[https://doi.org/10.1016/j.cej.2021.129085 New insights into oxytetracycline (OTC) adsorption behavior on polylactic acid microplastics undergoing microbial adhesion and degradation]<br>
C''hemical Engineering Journal'', 416, 129085.<br>
</li>
 
<li>Singh, R., Yadav, V., & Siddhanta, S. '''2023'''<br>
[https://doi.org/10.1039/D2CP05705K Probing plasmon-induced surface reactions using two-dimensional correlation vibrational spectroscopy].<br>
''Physical Chemistry Chemical Physics'', 25(8), 6032-6043.</li>
 
<li>Amato, J., Iaccarino, N., D'Aria, F., D'Amico, F., Randazzo, A., Giancola, C., ... & Pagano, B. '''2022'''.<br>
[https://doi.org/10.1039/D2CP00058J Conformational plasticity of DNA secondary structures: Probing the conversion between i-motif and hairpin species by circular dichroism and ultraviolet resonance Raman spectroscopies].<br>
''Physical Chemistry Chemical Physics'', 24(11), 7028-7044.</li>
 
<li>Pin, J. M., Anstey, A., Park, C. B., & Lee, P. C. '''2020'''<br>
[https://pubs.acs.org/doi/10.1021/acs.macromol.0c01819 Exploration of Polymer Calorimetric Glass Transition Phenomenology by Two-Dimensional Correlation Analysis].<br>
''Macromolecules'', 54(1), 473-487.</li>
 
<li>Lan, Z., Zhang, Y., Chen, X., Li, S., Cao, H., Wang, S., & Meng, J. '''2022'''<br>
[https://doi.org/10.1007/s12161-022-02245-y Efficient Detection of Limonoid From Citrus Seeds by Handheld NIR: Compared with Benchtop NIR].<br>
''Food Analytical Methods'', 15(7), 1909-1921.</li>
 
<li>Chavez-Angel, E., Puertas, B., Kreuzer, M., Soliva Fortuny, R., Ng, R. C., Castro-Alvarez, A., & Sotomayor Torres, C. M. '''2022'''<br>
[https://doi.org/10.3390/foods11091304 Spectroscopic and thermal characterization of extra virgin olive oil adulterated with edible oils].<br>
''Foods'', 11(9), 1304.</li>
 
<li>Park, Y., Jin, S., Noda, I., & Jung, Y. M. '''2022'''<br>
[https://doi.org/10.1016/j.saa.2022.121750 Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS), part II. Recent noteworthy developments.<br>
''Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy'', 121750.</li>
 
<li>Park, Y., Jin, S., Noda, I., & Jung, Y. M. '''2020'''<br>
[https://doi.org/10.1016/j.molstruc.2020.128405 Emerging developments in two-dimensional correlation spectroscopy (2D-COS)].<br>
''Journal of Molecular Structure'', 1217, 128405.</li>
 
</ol>
 
== Acknowledgement ==
 
mat2dcorr is an open source software project which has been initiated and is maintained by [http://www.peter-lasch.de Peter Lasch] at the [http://www.rki.de/EN/Content/Institute/DepartmentsUnits/CenterBioSafety/zbs6/zbs6_node.html ''Proteomics and Spectroscopy''] unit at the [http://www.rki.de ''Robert Koch-Institute''] (Berlin/Germany). The Matlab-based mat2dcorr toolbox is distributed under the Creative Commons CC BY-NC-SA 4.0 license for non-commercial use. Please send references to any publications, presentations, or successful funding applications that make use of the mat2Dcorr toolbox ([mailto:lasch@peter-lasch.de e-mail]).
 
In addition, I kindly ask to acknowledge utilization of the mat2dcorr toolbox by citing the following paper: <br> &nbsp; <br>
 
<ul><ul>
{| class="wikitable" width=800
|-
| [http://doi.org/10.1177/0003702818819880 Two-Dimensional Correlation Spectroscopy (2D-COS) for Analysis of Spatially Resolved Vibrational Spectra]. Lasch, P. and Noda, I. ''Appl Spectrosc''. '''2019'''.  73(4): 359-379. doi:10.1177/0003702818819880
|}
&nbsp; <br>
</ul></ul>
Bug reports are welcome! ([mailto:lasch@peter-lasch.de e-mail])

Revision as of 17:52, 2 April 2023

Two-dimensional correlation spectroscopy (2D-COS), or two-dimensional correlation analysis is known as a set of mathematical techniques useful to study changes in dynamic spectra. Dynamic spectra are often represented by spectra series obtained from a sample that was subjected to an external perturbation.
 
The 2D-COS analysis technique has been initially developed by Isao Noda in the 1980s.

Relevant Publications

Main concepts of two-dimensional correlation analysis
Basic principles of generalized 2D correlation spectroscopy are outlined in the following series of scientific publications:

 

Publications in which the mat2dcorr toolbox has been used or mentioned

  1. Lasch, P. and I. Noda 2017
    Two-Dimensional Correlation Spectroscopy for Multimodal Analysis of FT-IR, Raman, and MALDI-TOF MS Hyperspectral Images with Hamster Brain Tissue.
    Anal Chem. 89(9): 5008-5016.
  2. Lasch, P. and I. Noda 2019
    Two-Dimensional Correlation Spectroscopy (2D-COS) for Analysis of Spatially Resolved Vibrational Spectra.
    Appl Spectrosc. 73(4): 359-379.
  3. Sun, Y., Wang, X., Xia, S., & Zhao, J. 2021
    New insights into oxytetracycline (OTC) adsorption behavior on polylactic acid microplastics undergoing microbial adhesion and degradation
    Chemical Engineering Journal, 416, 129085.
  4. Singh, R., Yadav, V., & Siddhanta, S. 2023
    Probing plasmon-induced surface reactions using two-dimensional correlation vibrational spectroscopy.
    Physical Chemistry Chemical Physics, 25(8), 6032-6043.
  5. Amato, J., Iaccarino, N., D'Aria, F., D'Amico, F., Randazzo, A., Giancola, C., ... & Pagano, B. 2022.
    Conformational plasticity of DNA secondary structures: Probing the conversion between i-motif and hairpin species by circular dichroism and ultraviolet resonance Raman spectroscopies.
    Physical Chemistry Chemical Physics, 24(11), 7028-7044.
  6. Pin, J. M., Anstey, A., Park, C. B., & Lee, P. C. 2020
    Exploration of Polymer Calorimetric Glass Transition Phenomenology by Two-Dimensional Correlation Analysis.
    Macromolecules, 54(1), 473-487.
  7. Lan, Z., Zhang, Y., Chen, X., Li, S., Cao, H., Wang, S., & Meng, J. 2022
    Efficient Detection of Limonoid From Citrus Seeds by Handheld NIR: Compared with Benchtop NIR.
    Food Analytical Methods, 15(7), 1909-1921.
  8. Chavez-Angel, E., Puertas, B., Kreuzer, M., Soliva Fortuny, R., Ng, R. C., Castro-Alvarez, A., & Sotomayor Torres, C. M. 2022
    Spectroscopic and thermal characterization of extra virgin olive oil adulterated with edible oils.
    Foods, 11(9), 1304.
  9. Park, Y., Jin, S., Noda, I., & Jung, Y. M. 2022
    [https://doi.org/10.1016/j.saa.2022.121750 Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS), part II. Recent noteworthy developments.
    Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 121750.
  10. Park, Y., Jin, S., Noda, I., & Jung, Y. M. 2020
    Emerging developments in two-dimensional correlation spectroscopy (2D-COS).
    Journal of Molecular Structure, 1217, 128405.

Acknowledgement

mat2dcorr is an open source software project which has been initiated and is maintained by Peter Lasch at the Proteomics and Spectroscopy unit at the Robert Koch-Institute (Berlin/Germany). The Matlab-based mat2dcorr toolbox is distributed under the Creative Commons CC BY-NC-SA 4.0 license for non-commercial use. Please send references to any publications, presentations, or successful funding applications that make use of the mat2Dcorr toolbox (e-mail).

In addition, I kindly ask to acknowledge utilization of the mat2dcorr toolbox by citing the following paper:
 

Bug reports are welcome! (e-mail)

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