Recorded Webinar: Mass Spectrometry Data Pre-Processing and Analysis Using MATLAB

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This webinar demonstrates the benefits of using MATLAB for SELDI-TOF mass spectrometry pre-processing and data standardization.  Specifically, this webinar shows examples of:

• Signal re-sampling
• Background correction
• Calibration (peak alignment)

This webinar also demonstrated multiple methods for feature selection, including:

• Independent feature selection
• Classification reinforced feature selection
• Feature selection using genetic algorithms  

The Bioinformatics Toolbox contains a variety of functionality for pre-processing and feature selection of mass spectrometry data.  Using this pre-built functionality avoids researchers having to reinvent the wheel by implementing their own algorithms.  Rather, they can perform advanced data analysis quickly and easily.  Mass spectrometry also commonly involves analysis and comparing large numbers of mass spectrometry profiles (hundreds) to achieve statistically significant results, so MATLAB’s large dataset handling and distributed capabilities are highly suitable for this type of data analysis.

 

Product Focus

• Bioinformatics Toolbox
• Statistics Toolbox

This webinar was recorded on 24 Jun 2005

Duration: 48 Minutes