↓ Skip to main content

Technical phosphoproteomic and bioinformatic tools useful in cancer research

Overview of attention for article published in Journal of Clinical Bioinformatics, January 2011
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
41 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Technical phosphoproteomic and bioinformatic tools useful in cancer research
Published in
Journal of Clinical Bioinformatics, January 2011
DOI 10.1186/2043-9113-1-26
Pubmed ID
Authors

Elena López, Jan-Jaap Wesselink, Isabel López, Jesús Mendieta, Paulino Gómez-Puertas, Sarbelio Muñoz

Abstract

Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS) coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 5%
India 2 5%
United States 2 5%
Japan 1 2%
Italy 1 2%
Unknown 33 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 24%
Student > Ph. D. Student 9 22%
Student > Bachelor 6 15%
Professor > Associate Professor 3 7%
Student > Master 3 7%
Other 8 20%
Unknown 2 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 54%
Biochemistry, Genetics and Molecular Biology 4 10%
Medicine and Dentistry 4 10%
Chemistry 4 10%
Computer Science 2 5%
Other 2 5%
Unknown 3 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 October 2011.
All research outputs
#1,786,702
of 4,505,992 outputs
Outputs from Journal of Clinical Bioinformatics
#18
of 61 outputs
Outputs of similar age
#19,447
of 68,374 outputs
Outputs of similar age from Journal of Clinical Bioinformatics
#3
of 7 outputs
Altmetric has tracked 4,505,992 research outputs across all sources so far. This one has received more attention than most of these and is in the 58th percentile.
So far Altmetric has tracked 61 research outputs from this source. They receive a mean Attention Score of 1.9. This one has gotten more attention than average, scoring higher than 68% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 68,374 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.