Abstract
We proposed automatic factorization method of biological signals measured by Fluorescence Correlation Spectroscopy (FCS). Since the signals are composed from several positive components, the signals are decomposed by using the idea of Non-negative matrix factorization (NMF). Each component is represented by model functions and the signals are factorized as the non-negative sum of the model functions. Analytical accuracy of our proposed method was verified by using biological data that were measured by FCS. The experimental results showed that our method could automatically factorize the signals and the obtained components were similar with the ones obtained manually.
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Watanabe, K., Kurita, T. (2008). Automatic Factorization of Biological Signals Measured by Fluorescence Correlation Spectroscopy Using Non-negative Matrix Factorization. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4985. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69162-4_83
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DOI: https://doi.org/10.1007/978-3-540-69162-4_83
Publisher Name: Springer, Berlin, Heidelberg
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