LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise

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Mantini, Dante; Petrucci, Francesca; Pieragostino, Damiana; Del Boccio, Piero; Di Nicola, Marta; Di Ilio, Carmine; Federici, Giorgio; Sacchetta, Paolo; Comani, Silvia; Urbani, Andrea;
(2007)
  • Publisher: BMC
  • Journal: volume 8,issue 1,pages101-101issn: 1471-2105, eissn: 1471-2105
  • Publisher copyright policies & self-archiving
  • Related identifiers: pmc: PMC1847688, doi: 10.1186/1471-2105-8-101
  • Subject: Molecular Biology | Computational Biology | R858-859.7 | Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization | Computer applications to medicine. Medical informatics | Proteomics | Electricity | QH301-705.5 | Methodology Article | Proteins | Biochemistry | Computer Science Applications | Adult | Humans | Biology (General)

BACKGROUND: Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational metho... View more
  • References (26)
    26 references, page 1 of 3

    1. Rifai N, Gillette MA, Carr SA: Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nat Biotechnol 2006, 24(8):971-983.

    2. Diamandis EP: Mass spectrometry as a diagnostic and a cancer biomarker discovery tool: opportunities and potential limitations. Mol Cell Proteomics 2004, 3(4):367-378.

    3. Reyzer ML, Caprioli RM: MALDI mass spectrometry for direct tissue analysis: a new tool for biomarker discovery. J Proteome Res 2005, 4(4):1138-1142.

    4. Bonk T, Humeny A: MALDI-TOF-MS analysis of protein and DNA. Neuroscientist 2001, 7(1):6-12.

    5. Maddalo G, Petrucci F, Iezzi M, Pannellini T, Del Boccio P, Ciavardelli D, Biroccio A, Forli F, Di Ilio C, Ballone E, Urbani A, Federici G: Analytical assessment of MALDI-TOF Imaging Mass Spectrometry on thin histological samples. An insight in proteome investigation. Clin Chim Acta 2005, 357(2):210-218.

    6. Gras R, Muller M, Gasteiger E, Gay S, Binz PA, Bienvenut W, Hoogland C, Sanchez JC, Bairoch A, Hochstrasser DF, Appel RD: Improving protein identification from peptide mass fingerprinting through a parameterized multi-level scoring algorithm and an optimized peak detection. Electrophoresis 1999, 20(18):3535-3550.

    7. Satten GA, Datta S, Moura H, Woolfitt AR, Carvalho Mda G, Carlone GM, De BK, Pavlopoulos A, Barr JR: Standardization and denoising algorithms for mass spectra to classify whole-organism bacterial specimens. Bioinformatics 2004, 20(17):3128-3136.

    8. Yasui Y, McLerran D, Adam BL, Winget M, Thornquist M, Feng Z: An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers. J Biomed Biotechnol 2003, 2003(4):242-248.

    9. Kempka M, Sjodahl J, Bjork A, Roeraade J: Improved method for peak picking in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Rapid Commun Mass Spectrom 2004, 18(11):1208-1212.

    10. Coombes KR, Tsavachidis S, Morris JS, Baggerly KA, Hung MC, Kuerer HM: Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform. Proteomics 2005, 5(16):4107-4117.

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