The KSEA App: a web-based tool for kinase activity inference from quantitative phosphoproteomics.
Bioinformatics
; 33(21): 3489-3491, 2017 11 01.
Article
en En
| MEDLINE
| ID: mdl-28655153
ABSTRACT
Summary:
Computational characterization of differential kinase activity from phosphoproteomics datasets is critical for correctly inferring cellular circuitry and how signaling cascades are altered in drug treatment and/or disease. Kinase-Substrate Enrichment Analysis (KSEA) offers a powerful approach to estimating changes in a kinase's activity based on the collective phosphorylation changes of its identified substrates. However, KSEA has been limited to programmers who are able to implement the algorithms. Thus, to make it accessible to the larger scientific community, we present a web-based application of thismethod:
the KSEA App. Overall, we expect that this tool will offer a quick and user-friendly way of generating kinase activity estimates from high-throughput phosphoproteomics datasets. Availability and Implementation the KSEA App is a free online tool casecpb.shinyapps.io/ksea/. The source code is on GitHub github.com/casecpb/KSEA/. The application is also available as the R package "KSEAapp" on CRAN CRAN.R-project.org/package=KSEAapp/. Contact mark.chance@case.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2017
Tipo del documento:
Article