NDLI: Predictive value of recurrent DNA copy number variations

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Predictive value of recurrent DNA copy number variations

Content Provider	IEEE Xplore Digital Library
Author	Algallaf, A.K. Tewfik, A.H. Selleck, S.B. Johnson, R.L.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Minnesota Univ., Minneapolis, MN (Algallaf, A.K.; Tewfik, A.H.)
Abstract	Recurrent copy number variations across multiple samples are increasingly used to identify the genes and the genomic locations that are statistically and biologically significant and correlated with certain diseases. In this paper, we evaluate the predictive power of copy number variations for detecting autism. We consider both recurrent copy number variations at one location and correlated recurrent copy number variations at multiple locations. In each case, we compare the ability of k-means and Fuzzy c-means algorithms to correctly classify autistic samples. Finally, we apply our proposed techniques on 51 samples of 25 apparently healthy and 26 autistic children.
Starting Page	1
Ending Page	4
File Size	407932
Page Count	4
File Format	PDF
ISBN	9781424423712
DOI	10.1109/GENSIPS.2008.4555678
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Autism Filters Clustering methods DNA Genomics Humans Genetics Bioinformatics Diseases Testing
Content Type	Text
Resource Type	Article

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