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Identification of prognosis-specific network and prediction for estrogen receptor-negative breast cancer using microarray data and PPI data

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2015, 20(2), pp.137-147
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

황유현 1 오민 1 Youngmi Yoon 1

1가천대학교

Accredited

ABSTRACT

This study proposes an algorithm for predicting breast cancer prognosis based on genetic network. Weidentify prognosis-specific network using gene expression data and PPI(protein-protein interaction) data. To acquire the network, we calculate Pearson's correlation coefficient(PCC) between genes in all PPI pairs using gene expression data. We develop a prediction model for breast cancer patients withestrogen-receptor-negative using the network as a classifier. We compare classification performance ofour algorithm with existing algorithms on independent data and shows our algorithm is improved. Inaddition, we make an functionality analysis on the genes in the prognosis-specific network using GO(GeneOntology) enrichment validation.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.