발현프로파일과 기능주석을 결합한 최적화된 유전자 거리척도 = Optimized gene distance measures combining expression profiles and functional annotations

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Microarray is a technique which could measure thousands of genes’ expression level simultaneously. To find the co-regulated genes in microarray data, the clustering algorithms have been applied, such as hierarchical, K-means and SOM. Numerous different clustering results have been produced. It is a big challenge for biologists to choose meaningful clusters among the huge amount of results. The quantitative measurement of clustering result is called cluster validation. The cluster validation could be divided into two methods: data-driven approach and knowledge-driven approach based on the distance measurement between genes. We propose a new information fusion based distance metrics which could combine two knowledge information: data information and prior biological knowledge. And firstly incorporating the database of interacting protein to deal with the uncertainty of prior knowledge and using the optimization methods to find the optimal parameters for information fusion equation. To check the effect of the new method, two test datasets are used for experiments. In the comparison with conventional distance measurements, the new method shows better performance.
Advisors
Lee, Do-Heonresearcher이도헌researcher
Description
한국과학기술원 : 바이오시스템학과,
Publisher
한국과학기술원
Issue Date
2006
Identifier
260002/325007  / 020044342
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 바이오시스템학과, 2006.8, [ v, 25, [1] p. ]

Keywords

Gene distance measures; expression profiles and functional annotations; 기능주석; 발현프로파일; 유전자 거리척도

URI
http://hdl.handle.net/10203/27127
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=260002&flag=dissertation
Appears in Collection
BiS-Theses_Master(석사논문)
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