Parametric power spectral density analysis of noise from instrumentation in MALDI TOF mass spectrometry

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dc.citation.epage230en_US
dc.citation.spage219en_US
dc.citation.volumeNumber3en_US
dc.contributor.authorShin H.en_US
dc.contributor.authorMutlu, M.en_US
dc.contributor.authorKoomen J.M.en_US
dc.contributor.authorMarkey, M.K.en_US
dc.date.accessioned2016-02-08T10:11:02Z
dc.date.available2016-02-08T10:11:02Z
dc.date.issued2007en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractNoise in mass spectrometry can interfere with identification of the biochemical substances in the sample. For example, the electric motors and circuits inside the mass spectrometer or in nearby equipment generate random noise that may distort the true shape of mass spectra. This paper presents a stochastic signal processing approach to analyzing noise from electrical noise sources (i.e., noise from instrumentation) in MALDI TOF mass spectrometry. Noise from instrumentation was hypothesized to be a mixture of thermal noise, 1/f noise, and electric or magnetic interference in the instrument. Parametric power spectral density estimation was conducted to derive the power distribution of noise from instrumentation with respect to frequencies. As expected, the experimental results show that noise from instrumentation contains 1/f noise and prominent periodic components in addition to thermal noise. These periodic components imply that the mass spectrometers used in this study may not be completely shielded from the internal or external electrical noise sources. However, according to a simulation study of human plasma mass spectra, noise from instrumentation does not seem to affect mass spectra significantly. In conclusion, analysis of noise from instrumentation using stochastic signal processing here provides an intuitive perspective on how to quantify noise in mass spectrometry through spectral modeling.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:11:02Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2007en
dc.identifier.issn11769351
dc.identifier.urihttp://hdl.handle.net/11693/23261
dc.language.isoEnglishen_US
dc.source.titleCancer Informaticsen_US
dc.subjectArtifactsen_US
dc.subjectComputer simulationen_US
dc.subjectFourier analysisen_US
dc.subjectMassen_US
dc.subjectModels, computeren_US
dc.subjectNoiseen_US
dc.subjectSignal processing, computer-assisteden_US
dc.subjectSpectrometry, mass, matrix-assisted laser desorption-ionizationen_US
dc.subjectarticleen_US
dc.subjectelectric conductivityen_US
dc.subjectinstrumentationen_US
dc.subjectmass spectrometryen_US
dc.subjectmatrix assisted laser desorption ionization time of flight mass spectrometryen_US
dc.subjectnoise measurementen_US
dc.subjectnoise reductionen_US
dc.subjectparameteren_US
dc.subjectplasmaen_US
dc.subjectsignal noise ratioen_US
dc.subjectsimulationen_US
dc.subjectspectrometryen_US
dc.subjectstatisticsen_US
dc.subjectthermal conductivityen_US
dc.titleParametric power spectral density analysis of noise from instrumentation in MALDI TOF mass spectrometryen_US
dc.typeArticleen_US

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