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HDP-Align: Hierarchical Dirichlet Process Clustering for Multiple Peak Alignment of Liquid Chromatography Mass Spectrometry Data

https://doi.org/10.1101/074831
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Toward Global Metabolomics Analysis with Hydrophilic Interaction Liquid Chromatography–Mass Spectrometry: Improved Metabolite Identification by Retention Time Prediction
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Sample classification from protein mass spectrometry, by ‘peak probability contrasts’
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Progressive peak clustering in GC-MS Metabolomic experiments applied to Leishmania parasites
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Semi-supervised LC/MS alignment for differential proteomics
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Retention time alignment algorithms for LC/MS data must consider non-linear shifts
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A Bayesian approach to the alignment of mass spectra
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SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists
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Novel algorithms and the benefits of comparative validation
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Multi-profile Bayesian alignment model for LC-MS data analysis with integration of internal standards
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PeakLink: a new peptide peak linking method in LC-MS/MS using wavelet and SVM
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MetAssign: probabilistic annotation of metabolites from LC–MS data using a Bayesian clustering approach
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An Alignment Confidence Score Capturing Robustness to Guide Tree Uncertainty
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CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
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MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data
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Model-based peak alignment of metabolomic profiling from comprehensive two-dimensional gas chromatography mass spectrometry
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Critical assessment of alignment procedures for LC-MS proteomics and metabolomics measurements
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Hierarchical Dirichlet Processes
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Fast Statistical Alignment
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ClusterCluster: Parallel Markov Chain Monte Carlo for Dirichlet Process Mixtures
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Introduction to information retrieval
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