Abstract
The analysis mass spectra is dependent on the initial resolution and precision estimation. The novel method of relative entropy, combines the detection of the false precision, statistical binning problem, and the change of information content into one task. The methodological approach as well as relevant objectives are discussed in the first two parts of the work, including mathematical justification. The method of relative entropy has comparable results to the false precision detection, however using different approach. The binning problem solution is estimated via maximization of the relative entropy as a criterion parameter for objective magnitude rounding. The approach is verified on the real high resolution measurements with known presence of false precision. The method could be generalized for wider spectrum of data binnig/precision tasks.
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Acknowledgement
This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic - projects ‘CENAKVA’ (No. CZ.1.05/2.1.00/01.0024) and ‘CENAKVA II’ (No. LO1205 under the NPU I program).
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Urban, J. (2018). Resolution, Precision, and Entropy as Binning Problem in Mass Spectrometry. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10813. Springer, Cham. https://doi.org/10.1007/978-3-319-78723-7_10
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DOI: https://doi.org/10.1007/978-3-319-78723-7_10
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