CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 2
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LI Guo-qi, SHENG Huan-ye. Classification analysis of microarray data based on ontological engineering[J]. Journal of Zhejiang University Science A, 2007, 8(4): 638-643.
@article{title="Classification analysis of microarray data based on ontological engineering",
author="LI Guo-qi, SHENG Huan-ye",
journal="Journal of Zhejiang University Science A",
volume="8",
number="4",
pages="638-643",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A0638"
}
%0 Journal Article
%T Classification analysis of microarray data based on ontological engineering
%A LI Guo-qi
%A SHENG Huan-ye
%J Journal of Zhejiang University SCIENCE A
%V 8
%N 4
%P 638-643
%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A0638
TY - JOUR
T1 - Classification analysis of microarray data based on ontological engineering
A1 - LI Guo-qi
A1 - SHENG Huan-ye
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 4
SP - 638
EP - 643
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2007.A0638
Abstract: Background knowledge is important for data mining, especially in complicated situation. ontological engineering is the successor of knowledge engineering. The sharable knowledge bases built on ontology can be used to provide background knowledge to direct the process of data mining. This paper gives a common introduction to the method and presents a practical analysis example using SVM (support vector machine) as the classifier. Gene Ontology and the accompanying annotations compose a big knowledge base, on which many researches have been carried out. microarray dataset is the output of DNA chip. With the help of Gene Ontology we present a more elaborate analysis on microarray data than former researchers. The method can also be used in other fields with similar scenario.
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