Evidence map›Paper›PMID 28718811›Full record

ReviewProteomes2017

Tissue Specific Labeling in Proteomics.

Evelyn Ramberger, Gunnar Dittmar

Open access · goldAbstract readReview
In one paragraph

Review in Proteomes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

2 authors at 2 institutions in 2 countries.

Evelyn RambergerMass-Spectrometry Core Unit, Max Delbrück Center for Molecular Medicine, 13125 Berlin, Germany. evelyn.ramberger@mdc-berlin.de.
Gunnar DittmarProteome and Genome Research Laboratory, Luxembourg Institute of Health, 1272 Strassen, Luxembourg. gunnar.dittmar@lih.lu.
Luxembourg Institute of Health · LUMax Delbrück Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mass spectrometry-based proteomics is a powerful tool for identifying and quantifying proteins in biological samples. While it is routinely used for the characterization of simple cell line systems, the analysis of the cell specific proteome in multicellular organisms and tissues poses a significant challenge. Isolating a subset of cells from tissues requires mechanical and biochemical separation or sorting, a process which can alter cellular signaling, and thus, the composition of the proteome. Recently, several approaches for cell selective labeling of proteins, that include bioorthogonal amino acids, biotinylating enzymes, and genetic tools, have been developed. These tools facilitate the selective labeling of proteins, their interactome, or of specific cell types within a tissue or an organism, while avoiding the difficult and contamination-prone biochemical separation of cells from the tissue. In this review, we give an overview of existing techniques and their application in cell culture models and whole animals.

Indexed as

amino acid analogAPEXBioIDbioorthogonalbiotinylationmulticellularquantitative proteomicsSILACstable isotope labelingtissue

Identifiers

PMID28718811
PMCPMC5620534
OpenAlexW2738776417

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.