accelerator mass spectrometry
accelerator mass spectrometry in title
accelerator mass spectrometry in description
The used discriminant analysis is based on Principal Component Analysis with Mahalanobis Distance (PCA-MD) - part of multivariate analysis. Classifion has been tested using mass-spectra, but there is no limitation to be used with any other kind of characteristic spectra (e.g. VIS, IR, NMR). In latter case the x-values of the spec must be the detector channel number.
Almost every mass-spectrometry lab is equipped with spectral-library search program with tens of thousands of spectra of pure compounds. The problems begin when you have very complex substances or using mass-spec methods different from those used in the spec-libraries.
In some cases you dont need to know what exactly is in the sample, but simply does it belong to a class of samples you already measured. In all these cases you need to use classification software. But most of them are general purposed and require certain knowledge of the statistical methods used.
Here Classifion sits, offering you a classification with specialized for mass-spectrometry environment and automation allowing you to "avoid the depths of contemporary statistics", so you can concentrate on your immediate work.
Classifion needs to be "trained" using several measured spectra per substance. The "training" itself could be conducted automatically or manually (supervised).
The aim of the training is to extract substance specific information based on statistical characteristics, but not on the interpretation of the mass-spectra. Having some knowledge on the mass-spectra structure could improve classification precision.
Mathematically speaking the extraction is down to reducing the dimensionality of the spectra variable space (to each mass corresponds one dimension). PCA is well-known such technique, which offers other advantages as ordering the principal component by "significance" (useful for noise reduction).
Classifion can train itself entirely on autopilot. Just import your data, run Autopilot, sit back and enjoy the view. The results will show you how successful the training was, so in case of problem you should re-examine your data or do supervised training.
The feature which makes Classifion better than the most of PCA software out there, is the use of proper factor space for each substance separately, instead of traditional approach of using common factor space for all substances. That improves the classification precision and makes the work with Classifion similar to the spectral-library search software.
Classifion can be used remotely from another application (as COM server) combining remote with user access.
Limitations:
· 30 days trial
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accelerator mass spectrometry in software introduction
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