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Evaluating the performance of microarray segmentation algorithms
Author(s) -
Antti Lehmussola,
Pekka Ruusuvuori,
Olli YliHarja
Publication year - 2006
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btl502
Subject(s) - segmentation , computer science , ground truth , identification (biology) , pixel , image segmentation , data mining , artificial intelligence , gene chip analysis , pattern recognition (psychology) , microarray analysis techniques , algorithm , scale space segmentation , microarray , biology , botany , biochemistry , gene expression , gene
Although numerous algorithms have been developed for microarray segmentation, extensive comparisons between the algorithms have acquired far less attention. In this study, we evaluate the performance of nine microarray segmentation algorithms. Using both simulated and real microarray experiments, we overcome the challenges in performance evaluation, arising from the lack of ground-truth information. The usage of simulated experiments allows us to analyze the segmentation accuracy on a single pixel level as is commonly done in traditional image processing studies. With real experiments, we indirectly measure the segmentation performance, identify significant differences between the algorithms, and study the characteristics of the resulting gene expression data.

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