NDLI: A Systematic Approach for Identifying Regulatory Interactions in Large Temporal Gene Expression Datasets from Peripheral Blood

Content Provider	IEEE Xplore Digital Library
Author	Knott, S. Mousavi, P. Baranzini, S.
Copyright Year	2006
Description	Author affiliation: Dept of Computer Science, Queen's University, Kingston, Ontario, Canada, K7L 3N6. email: knott@cs.queensu.ca (Knott, S.) \|\| Dept of Neurology, University of California San Francisco, San Francisco, CA, USA, 94143. email: sebaran@cgl.ucsf.edu (Baranzini, S.) \|\| Member, IEEE, Dept of Computer Science, Queen's University, Kingston, Ontario, Canada, K7L 3N6. email: pmousavi@cs.queensu.ca (Mousavi, P.)
Abstract	High throughput genomic techniques produce datasets involving thousands of gene expression profiles. In order to infer biologically meaningful regulatory interactions, a dimensionality reduction must take place to identify genes or groups of genes that are important to the biological system being analyzed. Here we provide a systematic approach to remove dispersible genes from consideration based on their gene expression profiles, and to identify a smaller set of coordinately expressed genes, or metagenes that are biologically related to one and other based on previous biological knowledge. We then apply neural network based reverse engineering techniques to demonstrate that through these dimensionality reduction techniques novel genetic interactions can be identified.
Starting Page	1
Ending Page	8
File Size	11845068
Page Count	8
File Format	PDF
ISBN	1424406234
DOI	10.1109/CIBCB.2006.330979
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-09-28
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gene expression Blood Systematics Throughput Genomics Bioinformatics Biological systems Neural networks Reverse engineering Genetics
Content Type	Text
Resource Type	Article

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