Volume 13 Supplement 16

Statistical mass spectrometry-based proteomics

Research and reviews

Edited by Predrag Radivojac and Olga Vitek

This supplement did not receive any external funding

Content type: Research

A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet

PeptideProphet is a post-processing algorithm designed to evaluate the confidence in identifications of MS/MS spectra returned by a database search. In this manuscript we describe the "what and how" of Peptide...

Authors: Kelvin Ma, Olga Vitek and Alexey I Nesvizhskii

Citation: BMC Bioinformatics 2012 13(Suppl 16):S1

Published on: 5 November 2012
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Content type: Research

False discovery rates in spectral identification

Automated database search engines are one of the fundamental engines of high-throughput proteomics enabling daily identifications of hundreds of thousands of peptides and proteins from tandem mass (MS/MS) spec...

Authors: Kyowon Jeong, Sangtae Kim and Nuno Bandeira

Citation: BMC Bioinformatics 2012 13(Suppl 16):S2

Published on: 5 November 2012
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Content type: Research

A cross-validation scheme for machine learning algorithms in shotgun proteomics

Peptides are routinely identified from mass spectrometry-based proteomics experiments by matching observed spectra to peptides derived from protein databases. The error rates of these identifications can be es...

Authors: Viktor Granholm, William Stafford Noble and Lukas Käll

Citation: BMC Bioinformatics 2012 13(Suppl 16):S3

Published on: 5 November 2012
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Content type: Review

Computational approaches to protein inference in shotgun proteomics

Shotgun proteomics has recently emerged as a powerful approach to characterizing proteomes in biological samples. Its overall objective is to identify the form and quantity of each protein in a high-throughput...

Authors: Yong Fuga Li and Predrag Radivojac

Citation: BMC Bioinformatics 2012 13(Suppl 16):S4

Published on: 5 November 2012
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Content type: Research

Normalization and missing value imputation for label-free LC-MS analysis

Shotgun proteomic data are affected by a variety of known and unknown systematic biases as well as high proportions of missing values. Typically, normalization is performed in an attempt to remove systematic b...

Authors: Yuliya V Karpievitch, Alan R Dabney and Richard D Smith

Citation: BMC Bioinformatics 2012 13(Suppl 16):S5

Published on: 5 November 2012
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Content type: Research

Statistical protein quantification and significance analysis in label-free LC-MS experiments with complex designs

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) is widely used for quantitative proteomic investigations. The typical output of such studies is a list of identified and quantified peptid...

Authors: Timothy Clough, Safia Thaminy, Susanne Ragg, Ruedi Aebersold and Olga Vitek

Citation: BMC Bioinformatics 2012 13(Suppl 16):S6

Published on: 5 November 2012
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Content type: Review

Statistical methods for quantitative mass spectrometry proteomic experiments with labeling

Mass Spectrometry utilizing labeling allows multiple specimens to be subjected to mass spectrometry simultaneously. As a result, between-experiment variability is reduced. Here we describe use of fundamental c...

Authors: Ann L Oberg and Douglas W Mahoney

Citation: BMC Bioinformatics 2012 13(Suppl 16):S7

Published on: 5 November 2012
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Content type: Research

In silico design of targeted SRM-based experiments

Selected reaction monitoring (SRM)-based proteomics approaches enable highly sensitive and reproducible assays for profiling of thousands of peptides in one experiment. The development of such assays involves ...

Authors: Sven Nahnsen and Oliver Kohlbacher

Citation: BMC Bioinformatics 2012 13(Suppl 16):S8

Published on: 5 November 2012
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Content type: Research

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have sh...

Authors: D R Mani, Susan E Abbatiello and Steven A Carr

Citation: BMC Bioinformatics 2012 13(Suppl 16):S9

Published on: 5 November 2012
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Content type: Review

A tutorial in displaying mass spectrometry-based proteomic data using heat maps

Data visualization plays a critical role in interpreting experimental results of proteomic experiments. Heat maps are particularly useful for this task, as they allow us to find quantitative patterns across pr...

Authors: Melissa Key

Citation: BMC Bioinformatics 2012 13(Suppl 16):S10

Published on: 5 November 2012
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Content type: Review

MALDI imaging mass spectrometry: statistical data analysis and current computational challenges

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging mass spectrometry, also called MALDI-imaging, is a label-free bioanalytical technique used for spatially-resolved chemical analysi...

Authors: Theodore Alexandrov

Citation: BMC Bioinformatics 2012 13(Suppl 16):S11

Published on: 5 November 2012
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Content type: Research

1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data

Quantitative proteomics now provides abundance ratios for thousands of proteins upon perturbations. These need to be functionally interpreted and correlated to other types of quantitative genome-wide data such...

Authors: Juergen Cox and Matthias Mann

Citation: BMC Bioinformatics 2012 13(Suppl 16):S12

Published on: 5 November 2012
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Content type: Review

Knowledge-based analysis of proteomics data

As it is the case with any OMICs technology, the value of proteomics data is defined by the degree of its functional interpretation in the context of phenotype. Functional analysis of proteomics profiles is in...

Authors: Marina Bessarabova, Alexander Ishkin, Lellean JeBailey, Tatiana Nikolskaya and Yuri Nikolsky

Citation: BMC Bioinformatics 2012 13(Suppl 16):S13

Published on: 5 November 2012
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BMC Bioinformatics

Statistical mass spectrometry-based proteomics

Research and reviews

A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet

False discovery rates in spectral identification

A cross-validation scheme for machine learning algorithms in shotgun proteomics

Computational approaches to protein inference in shotgun proteomics

Normalization and missing value imputation for label-free LC-MS analysis

Statistical protein quantification and significance analysis in label-free LC-MS experiments with complex designs

Statistical methods for quantitative mass spectrometry proteomic experiments with labeling

In silico design of targeted SRM-based experiments

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics

A tutorial in displaying mass spectrometry-based proteomic data using heat maps

MALDI imaging mass spectrometry: statistical data analysis and current computational challenges

1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data

Knowledge-based analysis of proteomics data

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