A robust neural networks approach for spatial and intensity-dependent normalization of cDNA microarray data

@article{Tarca2005ARN,
  title={A robust neural networks approach for spatial and intensity-dependent normalization of cDNA microarray data},
  author={Adi L Tarca and Janice E. K. Cooke},
  journal={Bioinformatics},
  year={2005},
  volume={21 11},
  pages={2674-83}
}
MOTIVATION Microarray experiments are affected by numerous sources of non-biological variation that contribute systematic bias to the resulting data. In a dual-label (two-color) cDNA or long-oligonucleotide microarray, these systematic biases are often manifested as an imbalance of measured fluorescent intensities corresponding to Sample A versus those corresponding to Sample B. Systematic biases also affect between-slide comparisons. Making effective corrections for these systematic biases is… CONTINUE READING

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References

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Showing 1-10 of 12 references

R: a language for data analysis and graphics

  • R. Ihaka, R. Gentleman
  • 1996
Highly Influential
4 Excerpts

2002a) Analysis of cDNA microarray images

  • Yang, Y.H
  • 2002

Statistical analysis of a gene expression microarray experiment

  • Kerr, M.K
  • 2002

Statistical methods for identifying expressed genes in replicated cDNA microarray experiments

  • S Dudoit
  • 2002

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