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New approaches to clustering microarray time-series data using multiple expression profile alignment

Date

Authors

Subhani, Numanul

Rueda, Luis

Ngom, Alioune

Burden, Conrad

Publisher

IEEE

Abstract

An important process in functional genomic studies is clustering microarray time-series data, where genes with similar expression profiles are expected to be functionally related. Clustering microarray time-series data via pairwise alignment of piecewise

Keywords

Keywords: Clustering; Cubic spline; Gene expression profiles; Piecewise linear; Profile alignment; Time-series data; Alignment; Artificial intelligence; Bioinformatics; Microarrays; Piecewise linear techniques; Splines; Yeast; Gene expression Clustering; Cubic spline; Gene expression profiles; Microarrays; Piece-wise linear; Profile alignment; Time-Series data

URI

http://hdl.handle.net/1885/83829

Collections

ANU Research Publications

Source

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2010

Type

Conference paper

DOI

10.1109/CIBCB.2010.5510385

Restricted until

2037-12-31

Downloads

File

Description

01_Subhani_New_approaches_to_clustering_2010.pdf (2.32 MB)