서지주요정보
Identification of active functional modules with protein interaction and gene expression data = 단백질 상호작용과 유전자 발현 데이터를 이용한 기능적 모듈의 발견
서명 / 저자 Identification of active functional modules with protein interaction and gene expression data = 단백질 상호작용과 유전자 발현 데이터를 이용한 기능적 모듈의 발견 / Su-Sie Jo.
저자명 Jo, Su-Sie ; 조수지
발행사항 [대전 : 한국과학기술원, 2004].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8015690

소장위치/청구기호

학술문화관(문화관) 보존서고

MBiS 04010

SMS전송

도서상태

이용가능

대출가능

반납예정일

초록정보

Motivation : In model organisms such as yeast, large database of protein-protein interactions has become an extremely important resource for the study of protein function, evolution, and gene regulatory dynamics. In this paper we demonstrate that by integrating protein interaction data with mRNA expression data, it is possible to identify active functional modules, i.e., gene groups that show significant changes in expression under specific conditions such as nitrogen starvation and other stress conditions. Compared to S.cerevisiae, protein interaction data of S. pombe and newly sequenced H. polymorpha are remarkably small or none. To overcome this problem we proposed pipeline to identify functional modules in active functional modules from predicting protein interaction by integrating mRNA expression data. Method: We proposed method to find active functional modules (active sub-networks) under certain conditions - especially nutritional restriction such as glucose addtion and nitrogen starvation using PPI data and mRNA expression data. Firstly based on comparative genomics approach, we derived protein-protein interaction map of H. polymorpha and S.Pombe from protein-protein interaction map of other source organism (S. cerevisiae). To infer protein-protein interaction map from source organism, we adopted interacting domain profile pair (IDPP) method [2] along with naive sequence comparison. Secondly based on the idea that genes with correlated expression changes over many conditions or time courses are likely to be related to similar functions or cellular processes, we proposed combined molecular network model from protein-protein interaction map and mRNA expression association rule map. In the final step, using this combined model we applied simulated annealing method to detect active sub-network that is highly related to certain functional pathway under given condition based on the p-value scoring function [4].

서지기타정보

서지기타정보
청구기호 {MBiS 04010
형태사항 vi, 32 p. : 삽도 ; 26 cm
언어 영어
일반주기 저자명의 한글표기 : 조수지
지도교수의 영문표기 : Do-Deon Lee
지도교수의 한글표기 : 이도헌
학위논문 학위논문(석사) - 한국과학기술원 : 바이오시스템학과,
서지주기 Reference : p. 29-32
주제 ACTIVE FUNCTIONAL MODULEESIAN NETWORK
INFORMATION RETRIEVAL
GENETIC NETWORK RECONSTRUCTIONICAL DETECTION
기능적 모듈명 영상
베이지안 네트웍
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