Bayesian nonparametric models for peak identification in maldi-tof mass spectroscopy
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[1] M. Clyde,et al. Stochastic expansions using continuous dictionaries: Lévy adaptive regression kernels , 2011, 1112.3149.
[2] Bani K. Mallick,et al. A Bayesian Mixture Model for Protein Biomarker Discovery , 2010 .
[3] Heng Huang,et al. Mass spectrometry data processing using zero-crossing lines in multi-scale of Gaussian derivative wavelet , 2010, Bioinform..
[4] Feng Liang,et al. Bayesian function estimation using continuous wavelet dictionaries , 2009 .
[5] Jeffrey S. Morris,et al. Bayesian Analysis of Mass Spectrometry Proteomic Data Using Wavelet‐Based Functional Mixed Models , 2008, Biometrics.
[6] David C Christiani,et al. Biomarker discovery for arsenic exposure using functional data. Analysis and feature learning of mass spectrometry proteomic data. , 2008, Journal of proteome research.
[7] Z. Q. John Lu. Bayesian Inference for Gene Expression and Proteomics , 2007 .
[8] Bani K. Mallick,et al. Bayesian Curve Classification Using Wavelets , 2007 .
[9] Leanna House,et al. Bayesian Inference for Gene Expression and Proteomics: Nonparametric Models for Proteomic Peak Identification and Quantification , 2006 .
[10] Robert L. Wolpert,et al. Nonparametric Function Estimation Using Overcomplete Dictionaries , 2006 .
[11] Jeffrey S. Morris,et al. An Introduction to High-Throughput Bioinformatics Data , 2006 .
[12] Jeffrey S. Morris,et al. Bayesian Mixture Models for Gene Expression and Protein Profiles , 2006 .
[13] Jeffrey S. Morris,et al. Analysis of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models , 2006 .
[14] Jeffrey S. Morris,et al. 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 , 2005, Proteomics.
[15] I. Johnstone,et al. Empirical Bayes selection of wavelet thresholds , 2005, math/0508281.
[16] Jeffrey S. Morris,et al. Feature extraction and quantification for mass spectrometry in biomedical applications using the mean spectrum , 2005, Bioinform..
[17] Jeffrey S. Morris,et al. Understanding the characteristics of mass spectrometry data through the use of simulation , 2005, Cancer informatics.
[18] M. Trosset,et al. Enhancement of sensitivity and resolution of surface-enhanced laser desorption/ionization time-of-flight mass spectrometric records for serum peptides using time-series analysis techniques. , 2005, Clinical chemistry.
[19] Robert Tibshirani,et al. Sample classification from protein mass spectrometry, by 'peak probability contrasts' , 2004, Bioinform..
[20] R. Wolpert,et al. Reflecting uncertainty in inverse problems: a Bayesian solution using Lévy processes , 2004 .
[21] Anders Björk,et al. Improved method for peak picking in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. , 2004, Rapid communications in mass spectrometry : RCM.
[22] Jeffrey S. Morris,et al. Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments , 2004, Bioinform..
[23] G. Siuzdak. The Expanding Role of Mass Spectrometry in Biotechnology , 2006 .
[24] Y. Yasui,et al. An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers , 2003, Journal of biomedicine & biotechnology.
[25] M. Campa,et al. Analysis of human serum proteins by liquid phase isoelectric focusing and matrix‐assisted laser desorption/ionization‐mass spectrometry , 2003, Proteomics.
[26] C. Dass. Principles and Practice of Biological Mass Spectrometry , 2000 .
[27] Nouna Kettaneh,et al. Statistical Modeling by Wavelets , 1999, Technometrics.
[28] L. Zhigilei,et al. Velocity distributions of analyte molecules in matrix-assisted laser desorption from computer simulations , 1998 .
[29] J. Franzen. Improved resolution for MALDI-TOF mass spectrometers: a mathematical study , 1997 .
[30] P. Green. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .
[31] Matthew P. Wand,et al. Kernel Smoothing , 1995 .
[32] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[33] A. G. Greenhill,et al. Handbook of Mathematical Functions with Formulas, Graphs, , 1971 .
[34] David M. Miller,et al. Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .