Graph-Based Clustering Approaches for Gene Network Reconstruction
碩士 === 國立臺灣大學 === 醫學工程學研究所 === 97 === To understand regulatory relationships between genes in real life. Biologists often use RNA interference (RNAi) or knockout genes to observe the response in the real life system. Informationists try to reconstruct regulatory relationship between genes from mRNA...
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ndltd-TW-097NTU055300372016-05-04T04:31:49Z http://ndltd.ncl.edu.tw/handle/17481425002494051273 Graph-Based Clustering Approaches for Gene Network Reconstruction 基於圖形群聚之基因網路重建演算法 Jhih-Siang Lai 賴至祥 碩士 國立臺灣大學 醫學工程學研究所 97 To understand regulatory relationships between genes in real life. Biologists often use RNA interference (RNAi) or knockout genes to observe the response in the real life system. Informationists try to reconstruct regulatory relationship between genes from mRNA expression profile by algorithms or mathematic models. There are several phases involved in gene regulation such as transcription, post-transcriptional modifications, translation, mRNA degradation and post-translational modifications .Time is essential for all these phases to be completed and many researches analyze regulation via these features. In this study, we use two methods to reconstruct regulatory relationships between genes. One is a graph partition algorithm named Normalized Cuts for partitioning off genes into functional gene network. The other method, PARE (Pattern Recognition Approach), an algorithm based on time-lagged non-linear feature of the profile, is to infer regulation between genes. In addition, we use yeast microarray to construct gene regulatory networks and check results from KEGG pathway database, BIOGRID interaction database and MIPS database. Comparing our F score result with Dynamic Bayesian Network developed by Kim, et al., it shows that our method performs better than theirs. Finally, we apply our method to a real case in yeast microarray in which yox1 and yhp1 are both deleted and we analyze its mRNA expression time profile. Although mechanisms between phases in cell cycle are not clear, yox1 and yhp1 are two genes known controlling duration of a cell in G1 phase by negative feedback. We successfully find networks associated with cell cycle and one of the networks is associated with cell mitosis. In the future, we hope to decipher more mechanisms between phases in cell cycle. Chung-Ming Chen 陳中明 2009 學位論文 ; thesis 67 zh-TW |
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碩士 === 國立臺灣大學 === 醫學工程學研究所 === 97 === To understand regulatory relationships between genes in real life. Biologists often use RNA interference (RNAi) or knockout genes to observe the response in the real life system. Informationists try to reconstruct regulatory relationship between genes from mRNA expression profile by algorithms or mathematic models. There are several phases involved in gene regulation such as transcription, post-transcriptional modifications, translation,
mRNA degradation and post-translational modifications .Time is essential for all these phases to be completed and many researches analyze regulation via these features.
In this study, we use two methods to reconstruct regulatory relationships between genes. One is a graph partition algorithm named Normalized Cuts for partitioning off genes into functional gene network. The other method, PARE (Pattern Recognition Approach), an algorithm based on time-lagged non-linear feature of the profile, is to infer regulation between genes. In addition, we use yeast microarray to construct gene regulatory networks and check results from KEGG pathway database, BIOGRID interaction database and MIPS database. Comparing our F score result with Dynamic Bayesian Network developed by Kim, et al., it shows that our method performs better than theirs.
Finally, we apply our method to a real case in yeast microarray in which yox1 and yhp1 are both deleted and we analyze its mRNA expression time profile. Although mechanisms between phases in cell cycle are not clear, yox1 and yhp1 are two genes known controlling duration of a cell in G1 phase by negative feedback. We successfully find networks associated with cell cycle and one of the networks is associated with cell mitosis. In the future, we hope to decipher more mechanisms between phases in cell cycle.
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author2 |
Chung-Ming Chen |
author_facet |
Chung-Ming Chen Jhih-Siang Lai 賴至祥 |
author |
Jhih-Siang Lai 賴至祥 |
spellingShingle |
Jhih-Siang Lai 賴至祥 Graph-Based Clustering Approaches for Gene Network Reconstruction |
author_sort |
Jhih-Siang Lai |
title |
Graph-Based Clustering Approaches for Gene Network Reconstruction |
title_short |
Graph-Based Clustering Approaches for Gene Network Reconstruction |
title_full |
Graph-Based Clustering Approaches for Gene Network Reconstruction |
title_fullStr |
Graph-Based Clustering Approaches for Gene Network Reconstruction |
title_full_unstemmed |
Graph-Based Clustering Approaches for Gene Network Reconstruction |
title_sort |
graph-based clustering approaches for gene network reconstruction |
publishDate |
2009 |
url |
http://ndltd.ncl.edu.tw/handle/17481425002494051273 |
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