EconPapers    
Economics at your fingertips  
 

Predicting Protein Kinase Specificity: Predikin Update and Performance in the DREAM4 Challenge

Jonathan J Ellis and Boštjan Kobe

PLOS ONE, 2011, vol. 6, issue 7, 1-8

Abstract: Predikin is a system for making predictions about protein kinase specificity. It was declared the “best performer” in the protein kinase section of the Peptide Recognition Domain specificity prediction category of the recent DREAM4 challenge (an independent test using unpublished data). In this article we discuss some recent improvements to the Predikin web server — including a more streamlined approach to substrate-to-kinase predictions and whole-proteome predictions — and give an analysis of Predikin's performance in the DREAM4 challenge. We also evaluate these improvements using a data set of yeast kinases that have been experimentally characterised, and we discuss the usefulness of Frobenius distance in assessing the predictive power of position weight matrices.

Date: 2011
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0021169 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 21169&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0021169

DOI: 10.1371/journal.pone.0021169

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().

 
Page updated 2025-03-19
Handle: RePEc:plo:pone00:0021169