Accurate quantification of gene expression using fuzzy clustering approaches

Yu Ping Wang, Maheswar Gunampally, Jie Chen, Douglas Bittet, Merlin G. Butler, Wei Wen Cai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Despite the widespread application of microarray imaging for biomedical research, barriers still exist regarding its reliability and reproducibility for clinical use. A critical problem lies in accurate spot segmentation and quantification of gene expression level (mRNA) from microarray images. A variety of commercial and research freeware packages are available, but most cannot handle array spots with complex shapes suck as donuts and scratches. Clustering approaches suck as k-means and mixture models were introduced to overcome this difficulty, which used the hard labeling of each pixel. In this paper, we introduce a more sophisticated fuzzy clustering based method. We show that possiblistic c-means clustering performed the best among several fuzzy clustering approaches. In addition, we compared three statistical criteria in measuring gene expression levels and show that a new unbiased statistic is able to quantify the gene expression level more accurately. The proposed algorithms have been tested on a variety of simulated and real microarray images, demonstrating their better performance.

Original languageEnglish (US)
Title of host publication5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07
DOIs
StatePublished - Dec 1 2007
Externally publishedYes
Event5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07 - Tuusula, Finland
Duration: Jun 10 2007Jun 12 2007

Other

Other5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07
CountryFinland
CityTuusula
Period6/10/076/12/07

Fingerprint

Fuzzy clustering
Microarrays
Gene expression
Cluster Analysis
Gene Expression
Labeling
Pixels
Statistics
Imaging techniques
Biomedical Research
Messenger RNA
Research

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science Applications
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Wang, Y. P., Gunampally, M., Chen, J., Bittet, D., Butler, M. G., & Cai, W. W. (2007). Accurate quantification of gene expression using fuzzy clustering approaches. In 5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07 [4365833] https://doi.org/10.1109/GENSIPS.2007.4365833

Accurate quantification of gene expression using fuzzy clustering approaches. / Wang, Yu Ping; Gunampally, Maheswar; Chen, Jie; Bittet, Douglas; Butler, Merlin G.; Cai, Wei Wen.

5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07. 2007. 4365833.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, YP, Gunampally, M, Chen, J, Bittet, D, Butler, MG & Cai, WW 2007, Accurate quantification of gene expression using fuzzy clustering approaches. in 5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07., 4365833, 5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07, Tuusula, Finland, 6/10/07. https://doi.org/10.1109/GENSIPS.2007.4365833
Wang YP, Gunampally M, Chen J, Bittet D, Butler MG, Cai WW. Accurate quantification of gene expression using fuzzy clustering approaches. In 5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07. 2007. 4365833 https://doi.org/10.1109/GENSIPS.2007.4365833
Wang, Yu Ping ; Gunampally, Maheswar ; Chen, Jie ; Bittet, Douglas ; Butler, Merlin G. ; Cai, Wei Wen. / Accurate quantification of gene expression using fuzzy clustering approaches. 5th IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'07. 2007.
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