NDLI: Reducing a Biomarkers List via Mathematical Programming: Application to Gene Signatures to Detect Time-Dependent Hypoxia in Cancer

Content Provider	IEEE Xplore Digital Library
Author	Fung, G. Seigneuricb, R. Krishna, S. Rao, R.B. Wouters, B.G. Lambin, P.
Copyright Year	2007
Description	Author affiliation: CAD & Knowledge Solutions, Malvern (Fung, G.; Seigneuricb, R.; Krishna, S.; Rao, R.B.)
Abstract	In biology and medical sciences, highly parallel biological assays spurred a revolution leading to the emergence of the '-omics' era. Dimensionality reduction techniques are necessary to be able to analyze, interpret, validate and take advantage of the tremendous wealth of highly dimensional data they provide. This paper is based on a DNA microarray study providing gene signatures for hypoxia. These gene signatures were tested on a large breast cancer data set for assessing their prognostic power by means of Kaplan-Meier survival, univariate, and multivariate analyses. We explore the use of several mathematical programming-based techniques that aim to reduce the gene signature sizes as much as possible while maintaining the key characteristics of the original signature, more precisely: the signature prognostic and diagnostic significance. The proposed signature reduction techniques have very interesting potential uses. Indeed, by downsizing the relevant data to a manageable size, one can then patent the core set of biomarkers and also create a dedicated assay (e.g.: on a customized array) for routine applications (e.g.: in the clinical set up) leading to individualized medicine capabilities. Our experiments show that the reduced hypoxia signatures reproduced qualitatively and quantitatively in a similar way that of the original ones.
Starting Page	482
Ending Page	487
File Size	609722
Page Count	6
File Format	PDF
ISBN	9780769530697
DOI	10.1109/ICMLA.2007.61
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	DNA Genomics Machine learning Biomarkers Cancer detection Oncology Biology Bioinformatics Medical diagnostic imaging Mathematical programming
Content Type	Text
Resource Type	Article

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