NDLI: Mining Plausible Patterns from Genomic Data

Content Provider	IEEE Xplore Digital Library
Author	Klema, J. Soulet, A. Cremilleux, B. Blachon, S. Gandrillon, O.
Copyright Year	2006
Description	Author affiliation: GREYC, Caen Univ. (Klema, J.; Soulet, A.; Cremilleux, B.)
Abstract	The discovery of biologically interpretable knowledge from gene expression data is one of the largest contemporary genomic challenges. As large volumes of expression data are being generated, there is a great need for automated tools that provide the means to analyze them. However, the same tools can provide an overwhelming number of candidate hypotheses which can hardly be manually exploited by an expert. An additional knowledge helping to focus automatically on the most plausible candidates only can up-value the experiment significantly. Background knowledge available in literature databases, biological ontologies and other sources can be used for this purpose. In this paper we propose and verify a methodology that enables to effectively mine and represent meaningful over-expression patterns. Each pattern represents a bi-set of a gene group over-expressed in a set of biological situations. The originality of the framework consists in its constraint-based nature and an effective cross-fertilization of constraints based on expression data and background knowledge. The result is a limited set of candidate patterns that are most likely interpretable by biologists. Supplemental automatic interpretations serve to ease this process. Various constraints can generate plausible pattern sets of different characteristics
Starting Page	183
Ending Page	190
File Size	318290
Page Count	8
File Format	PDF
ISBN	0769525171
ISSN	10637125
DOI	10.1109/CBMS.2006.116
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genomics Bioinformatics Biological information theory Gene expression Frequency Data mining Databases Ontologies Character generation Pattern analysis
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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