ArticleProteomics2015
Proteomics equipped with multiplexing toward ultra high throughput.
Article in Proteomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Comment on
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MS-based quantitative proteomics is a powerful technology to study virtually almost all biological and clinical samples. Although it has been known to be a high-throughput method, an MS analysis of a higher number of samples remains to be challenging practically and economically. In this issue, the use of multiplexing strategy for quantitative analysis of proteomes and phosphoproteomes has been demonstrated by Paulo et al. (Proteomics 2015, 15, 462-473) to better understand in vivo effects of two small molecule inhibitors on a mouse model. Within the short period of drug treatment, it has been found that the protein alteration is minimal in three tissues tested, whereas the phosphorylation level was widely altered.
Indexed as
Identifiers
25522341What OpenQuestion holds
Registered trials
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.