Evidence map›Paper›PMID 22231900›Full record

ReviewWiley interdisciplinary reviews. Systems biology and medicine

Mass spectrometry-based proteomics: qualitative identification to activity-based protein profiling.

Job D Cardoza, Jignesh R Parikh, Scott B Ficarro, Jarrod A Marto

Abstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. Systems biology and medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. In Vitro and In Vivo Models Studying Haemophilus influenzae.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Job D CardozaDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
Jignesh R Parikh
Scott B Ficarro
Jarrod A Marto

Funding

Genomic Analysis of Network Perturbations in Human DiseaseP50HG004233 · NHGRI · DANA-FARBER CANCER INST · PI VIDAL, MARC · 2007 to 2017
$31.6M
Transcriptional control of inhibitory synapse formationP01NS047572 · NINDS · DANA-FARBER CANCER INSTITUTE · PI STILES, CHARLES D · 2004 to 2013
$13.5M
NHGRI NIH HHS P50 HG004233NHGRI NIH HHS P50HG004233NINDS NIH HHS P01 NS047572NINDS NIH HHS P01NS047572
6 · The paper itself

Abstract

Mass spectrometry has become the method of choice for proteome characterization, including multicomponent protein complexes (typically tens to hundreds of proteins) and total protein expression (up to tens of thousands of proteins), in biological samples. Qualitative sequence assignment based on MS/MS spectra is relatively well-defined, while statistical metrics for relative quantification have not completely stabilized. Nonetheless, proteomics studies have progressed to the point whereby various gene-, pathway-, or network-oriented computational frameworks may be used to place mass spectrometry data into biological context. Despite this progress, the dynamic range of protein expression remains a significant hurdle, and impedes comprehensive proteome analysis. Methods designed to enrich specific protein classes have emerged as an effective means to characterize enzymes or other catalytically active proteins that are otherwise difficult to detect in typical discovery mode proteomics experiments. Collectively, these approaches will facilitate identification of biomarkers and pathways relevant to diagnosis and treatment of human disease.

Indexed as

ProteomicsChromatography, High Pressure LiquidHumansPhosphopeptidesProtein Interaction MapsProteinsProteomeTandem Mass SpectrometryPhosphopeptidesProteinsProteome

Identifiers

PMID22231900
PMCPMC3288153

What OpenQuestion holds

Textmetadata
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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.