NDLI: Outlier Filtering for Identification of Gene Regulations in Microarray Time-Series Data

Content Provider	IEEE Xplore Digital Library
Author	Yang, A.C. Hui-Huang Hsu Ming-Da Lu
Copyright Year	2009
Abstract	Microarray technology provides an opportunity for scientists to analyze thousands of gene expression profiles simultaneously. Time-series microarray data are gene expression values generated from microarray experiments within certain time intervals. Scientists can infer gene regulations in a biological system by judging whether two genes present similar gene expression values in microarray time-series data. Recently, a great many methods are widely applied on microarray time-series data to find out the similarity and the correlation degree among genes. Existing approaches including traditional Pearson coefficient correlation, Bayesian networks, clustering analysis, classification methods, and correlation analysis have individual disadvantages such as high computational complexity or they may be unsuitable for some microarray data. Traditional Pearson correlation coefficient is a numeric measuring method which gives novel effectiveness on two sets of numeric data. However, it is not suitable to be applied on microarray time-series data because of the existence of outliers among gene expression values. This paper presents a novel method of applying Pearson correlation coefficient along with an outlier filtering procedure on the widely-used microarray time-series datasets. Results show that the proposed method produces a better outcome compared with traditional Pearson correlation coefficient on the same dataset. Results show that the proposed method not only can find out certain more known regulatory gene pairs, but also keeps rational computational time.
Starting Page	854
Ending Page	859
File Size	356454
Page Count	6
File Format	PDF
ISBN	9781424435692
DOI	10.1109/CISIS.2009.70
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-16
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gene Expression Analysis Data engineering Information filtering Electronic mail Gene Regulation Identification Gene expression Microarray Computer science Time-Series Data Outlier Filtering Biological processes Biological systems Software systems Information filters Competitive intelligence
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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