Neural Networks for Mass Spectra Classification: Preliminary Results
نویسندگان
چکیده
In this paper we summarize some experiments we have carried out in order to classify mass spectra. First we describe the pre-processing and the features extraction we have realized using the Bioinformatics toolbox of MATLAB. Then we describe results we have obtained using feed forward neural networks trained with a classical back-propagation; to avoid reinventing the wheel, WEKA has been used for this task. Preliminary results obtained by the analysis of a data set of tumor/healthy samples allowed us to correctly classify more than 80% of samples. A more detailed analysis of our results show that our method at least deserves attention and further studies.
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