Identification of different sets of biomarkers for diagnostic classification of cancers

Yu Shuen Tsai*, I. Fang Chung, Chin Teng Lin, Nikhil Ranjan Pal

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Accurate diagnosis of neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma, is often difficult because these cancers appear similar in routine histology. Finding a few useful biomarkers (not all related genes) that can discriminate between the subgroups will help designing better diagnostic systems. In an earlier study we reported a set of seven genes having excellent discrimination power. In this investigation we extend that study and find other distinct sets of genes with strong class specific signatures. This is achieved analyzing the correlation between genes. This led us to find another set of seven genes with better discriminating power. Our original gene selection method used a neural network whose output may significantly depend on initialization of the network, network size as well as the training data set. To address these issues we propose a scheme based on re-sampling. This method can also reduce the effect wide variation in number of data points in the training set from different classes. This method led us to find a set of five genes with good discriminating power. The genes identified by the proposed methods have roles in cancer biology.

原文English
主出版物標題Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers
頁面866-875
頁數10
版本PART 2
DOIs
出版狀態Published - 2008
事件14th International Conference on Neural Information Processing, ICONIP 2007 - Kitakyushu, Japan
持續時間: 13 11月 200716 11月 2007

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
號碼PART 2
4985 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference14th International Conference on Neural Information Processing, ICONIP 2007
國家/地區Japan
城市Kitakyushu
期間13/11/0716/11/07

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