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SlopeMiner: An Improved Method for Mining Subtle Signals in Time Course Microarray Data.

Authors :
McCormick, Kevin
Shrivastava, Roli
Liao, Li
Source :
Frontiers in Algorithmics (9783540693109); 2008, p28-34, 7p
Publication Year :
2008

Abstract

This paper presents an improved method, SlopeMiner, for analyzing time course microarray data by identifying genes that undergo gradual transitions in expression level. The algorithm calculates the slope for the slow transition between the expression levels of data, matching the sequence of expression level for each gene against temporal patterns having one transition between two expression levels. The method, when used along with StepMiner -an existing method for extracting binary signals, significantly increases the annotation accuracy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540693109
Database :
Complementary Index
Journal :
Frontiers in Algorithmics (9783540693109)
Publication Type :
Book
Accession number :
76721483
Full Text :
https://doi.org/10.1007/978-3-540-69311-6_6