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Output details

15 - General Engineering

Brunel University London

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Output 234 of 258 in the submission

Article title

The Application of Artificial Intelligence to Microarray Data: Identification of a Novel Gene Signature to Identify Bladder Cancer Progression

Type

D - Journal article

DOI

10.1016/j.eururo.2009.10.029

Title of journal

European Urology

Article number

Volume number

Issue number

First page of article

398

ISSN of journal

03022838

Year of publication

2009

URL

http://pdn.sciencedirect.com/science?_ob=MiamiImageURL&_cid=272280&_user=545641&_pii=S030228380901135X&_check=y&_origin=article&_zone=toolbar&_coverDate=2010--31&view=c&originContentFamily=serial&wchp=dGLbVBA-zSkzS&md5=6d7b7ca00756024f1bd7bf292487cef2&pid=

Number of additional authors

Additional information

This paper reports a break through in gene expression microarrays for revealing insights into disease biology and identifies novel biomarkers. A novel technique has been developed by combining an AI ensemble (ANN and NFS) that has predicted bladder cancer progression genes which were validated using immunohistochemistry. The identified prognostic genes signatures reflect a variety of carcinogenic pathways that can identify progression in non–muscle-invasive cancer.

Interdisciplinary

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract