Reliability analysis of microarray data using fuzzy c-means and normal mixture modeling based classification methods


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ASYALI M., Alci M.

BIOINFORMATICS, cilt.21, ss.644-649, 2005 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 21 Konu: 5
  • Basım Tarihi: 2005
  • Doi Numarası: 10.1093/bioinformatics/bti036
  • Dergi Adı: BIOINFORMATICS
  • Sayfa Sayıları: ss.644-649

Özet

Motivation: A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. Therefore, the elimination of unreliable signal intensities will enhance reproducibility and reliability of gene expression ratios produced from microarray data. In this study, we applied fuzzy c-means (FCM) and normal mixture modeling (NMM) based classification methods to separate microarray data into reliable and unreliable signal intensity populations.