Evidence map›Paper›PMID 15314609›Full record

ArticleNature biotechnology2004

Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics.

Blagoy Blagoev, Shao-En Ong, Irina Kratchmarova, Matthias Mann

Abstract readLetter
PubMed Publisher
In one paragraph

Article in Nature biotechnology, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 205 papers.

0numbers the graph read from it
0cells of the map it votes in
205citing papers in PubMed
36.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

205 citing papers in PubMed, 683 citations in OpenAlex.

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145 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Blagoy Blagoev
Shao-En Ong
Irina Kratchmarova
Matthias Mann
University of Southern Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To study the global dynamics of phosphotyrosine-based signaling events in early growth factor stimulation, we developed a mass spectrometric method that converts temporal changes to differences in peptide isotopic abundance. The proteomes of three cell populations were metabolically encoded with different stable isotopic forms of arginine. Each population was stimulated by epidermal growth factor for a different length of time, and tyrosine-phosphorylated proteins and closely associated binders were affinity purified. Arginine-containing peptides occurred in three forms, which were quantified; we then combined two experiments to generate five-point dynamic profiles. We identified 81 signaling proteins, including virtually all known epidermal growth factor receptor substrates, 31 novel effectors and the time course of their activation upon epidermal growth factor stimulation. Global activation profiles provide an informative perspective on cell signaling and will be crucial to modeling signaling networks in a systems biology approach.

Indexed as

Epidermal Growth FactorErbB ReceptorsGene Expression RegulationHeLa CellsHumansIsotope LabelingKineticsMass SpectrometryOxidative PhosphorylationPhosphotyrosineProteomeProteomicsSignal TransductionTime FactorsEpidermal Growth FactorErbB ReceptorsPhosphotyrosineProteome

Identifiers

PMID15314609
OpenAlexW1978254752

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.