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Title 

APPEX: analysis platform for the identification of prognostic gene expression signatures in cancer

Authors 

Seon Kyu KimJong Hwan KimS J YoonW J KimSeon-Young Kim

Publisher 

Oxford University Press (OUP)

Issue Date 

2014

Citation 

Bioinformatics, vol. 30, no. 22, pp. 3284-3286

Abstract 

Because cancer has heterogeneous clinical behaviors due to the progressive accumulation of multiple genetic and epigenetic alterations, the identification of robust molecular signatures for predicting cancer outcome is profoundly important. Here, we introduce the APPEX Web-based analysis platform as a versatile tool for identifying prognostic molecular signatures that predict cancer diversity. We incorporated most of statistical methods for survival analysis and implemented seven survival analysis workflows, including CoxSingle, CoxMulti, IntransSingle, IntransMulti, SuperPC, TimeRoc and multivariate. A total of 236 publicly available datasets were collected, processed and stored to support easy independent validation of prognostic signatures. Two case studies including disease recurrence and bladder cancer progression were described using different combinations of the seven workflows.

ISSN 

1367-4803

Link 

http://dx.doi.org/10.1093/bioinformatics/btu521

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2019-05-02


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