Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines (Q37029033)

https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:22552787%20AND%20SRC:MED&resulttype=core&format=json

31 January 2020

title

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines (English)

1 reference

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31 January 2020

5

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31 January 2020

David Tabb

6

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31 January 2020

author name string

Yao-Yi Chen

1

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31 January 2020

Surendra Dasari

2

1 reference

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31 January 2020

Ze-Qiang Ma

3

1 reference

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31 January 2020

Lorenzo J Vega-Montoto

4

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31 January 2020

language of work or name

English

0 references

publication date

3 May 2012

1 reference

https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:22552787%20AND%20SRC:MED&resulttype=core&format=json

Analytical and Bioanalytical Chemistry

31 January 2020

published in

1 reference

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31 January 2020

volume

404

1 reference

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31 January 2020

issue

4

1 reference

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31 January 2020

page(s)

1115-1125

1 reference

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An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database

31 January 2020

cites work

1 reference

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Supporting tool suite for production proteomics

29 September 2017

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MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines

29 September 2017

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Abacus: a computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis

29 September 2017

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Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

29 September 2017

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ZEB1 represses E-cadherin and induces an EMT by recruiting the SWI/SNF chromatin-remodeling protein BRG1

29 September 2017

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TagRecon: high-throughput mutation identification through sequence tagging

29 September 2017

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Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry

29 September 2017

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IDPicker 2.0: Improved protein assembly with high discrimination peptide identification filtering

29 September 2017

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ProteoWizard: open source software for rapid proteomics tools development

29 September 2017

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Statistical validation of peptide identifications in large-scale proteomics using the target-decoy database search strategy and flexible mixture modeling

29 September 2017

1 reference

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Assigning significance to peptides identified by tandem mass spectrometry using decoy databases

29 September 2017

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=3717168

Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution

29 September 2017

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Proteomic parsimony through bipartite graph analysis improves accuracy and transparency

29 September 2017

1 reference

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Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry

29 September 2017

1 reference

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MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis

29 September 2017

1 reference

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Meta-analysis based on control of false discovery rate: combining yeast ChIP-chip datasets

29 September 2017

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Large-scale cDNA transfection screening for genes related to cancer development and progression

29 September 2017

1 reference

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DBParser: web-based software for shotgun proteomic data analyses

29 September 2017

1 reference

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A model for random sampling and estimation of relative protein abundance in shotgun proteomics

29 September 2017

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Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression

29 September 2017

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TANDEM: matching proteins with tandem mass spectra

29 September 2017

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A statistical model for identifying proteins by tandem mass spectrometry

29 September 2017

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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=3717168

Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search

29 September 2017

1 reference

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Controlling the false discovery rate in behavior genetics research

29 September 2017

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Probability-based protein identification by searching sequence databases using mass spectrometry data

29 September 2017

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Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines

29 September 2017

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The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS.

27 June 2018

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Spectral index for assessment of differential protein expression in shotgun proteomics.

27 June 2018

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Improving sensitivity by probabilistically combining results from multiple MS/MS search methodologies

4 September 2018

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Correlation of Relative Abundance Ratios Derived from Peptide Ion Chromatograms and Spectrum Counting for Quantitative Proteomic Analysis Using Stable Isotope Labeling

4 September 2018

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Crossref

https://api.crossref.org/works/10.1007%2FS00216-012-6011-X

Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach

21 January 2018

1 reference

Crossref

https://api.crossref.org/works/10.1007%2FS00216-012-6011-X

The implications of proteolytic background for shotgun proteomics

21 January 2018

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/22552787

inferred from PubMed ID database lookup

12 December 2020

based on heuristic

Identifiers

DOI

10.1007/S00216-012-6011-X

1 reference

https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:22552787%20AND%20SRC:MED&resulttype=core&format=json

31 January 2020

1 reference

https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:22552787%20AND%20SRC:MED&resulttype=core&format=json

31 January 2020

PubMed publication ID

22552787

1 reference

https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:22552787%20AND%20SRC:MED&resulttype=core&format=json