TY  - JOUR
T1  - Identification of Heterogeneous Prognostic Genes and Prediction of Cancer Outcome using PageRank
AU  - Choi, Jonghwan 
AU  - Ahn, Jaegyoon 
JO  - Journal of KIISE, JOK
PY  - 2018
DA  - 2018/1/14
DO  - 10.5626/JOK.2018.45.1.61
KW  - PageRank
KW  - cancer
KW  - heterogeneity
KW  - prognosis prediction
KW  - biomarker
KW  - classification
AB  - The identification of genes that contribute to the prediction of prognosis in patients with cancer is one of the challenges in providing appropriate therapies. To find the prognostic genes, several classification models using gene expression data have been proposed. However, the prediction accuracy of cancer prognosis is limited due to the heterogeneity of cancer. In this paper, we integrate microarray data with biological network data using a modified PageRank algorithm to identify prognostic genes. We also predict the prognosis of patients with 6 cancer types (including breast carcinoma) using the K-Nearest Neighbor algorithm. Before we apply the modified PageRank, we separate samples by K-Means clustering to address the heterogeneity of cancer. The proposed algorithm showed better performance than traditional algorithms for prognosis. We were also able to identify cluster-specific biological processes using GO enrichment analysis.