Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks

碩士 === 國立臺灣大學 === 資訊管理學研究所 === 95 === Many high throughput experiments have been used to detect protein interactions which can be used to a protein-protein interaction network. To recognize the protein complexes in a protein-protein interaction network can help us understand the mechanisms of the bi...

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Main Authors: Chia-Ming Hsu, 許家銘
Other Authors: 李瑞庭
Format: Others
Language:en_US
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/36566464250907433472
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spelling ndltd-TW-095NTU053960302015-12-07T04:04:11Z http://ndltd.ncl.edu.tw/handle/36566464250907433472 Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks 由蛋白質交互網路中探勘可重疊之密集子網路 Chia-Ming Hsu 許家銘 碩士 國立臺灣大學 資訊管理學研究所 95 Many high throughput experiments have been used to detect protein interactions which can be used to a protein-protein interaction network. To recognize the protein complexes in a protein-protein interaction network can help us understand the mechanisms of the biological processes. In this thesis, we proposed a novel method with four phases to mine the protein complexes in the protein-protein interaction network. First, we calculate the weighted degree for each vertex in the network and pick the vertex with the highest weighted degree as the seed vertex. Second, we find a dense subgraph based on the greedy algorithm. Third, we modify the edge weights in the network and compute the weighted degree and the ratio of weighted degree for each vertex in the network. Finally, we repeat the above phases until no more dense subgraph can be found. Our proposed method does not remove any vertex and edge as a subgraph has been found. Therefore our method can mine more overlapping subgraphs than the CODENSE method. The experiment results show that our proposed method can find more protein complexes than the CODENSE method. 李瑞庭 2007 學位論文 ; thesis 29 en_US
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description 碩士 === 國立臺灣大學 === 資訊管理學研究所 === 95 === Many high throughput experiments have been used to detect protein interactions which can be used to a protein-protein interaction network. To recognize the protein complexes in a protein-protein interaction network can help us understand the mechanisms of the biological processes. In this thesis, we proposed a novel method with four phases to mine the protein complexes in the protein-protein interaction network. First, we calculate the weighted degree for each vertex in the network and pick the vertex with the highest weighted degree as the seed vertex. Second, we find a dense subgraph based on the greedy algorithm. Third, we modify the edge weights in the network and compute the weighted degree and the ratio of weighted degree for each vertex in the network. Finally, we repeat the above phases until no more dense subgraph can be found. Our proposed method does not remove any vertex and edge as a subgraph has been found. Therefore our method can mine more overlapping subgraphs than the CODENSE method. The experiment results show that our proposed method can find more protein complexes than the CODENSE method.
author2 李瑞庭
author_facet 李瑞庭
Chia-Ming Hsu
許家銘
author Chia-Ming Hsu
許家銘
spellingShingle Chia-Ming Hsu
許家銘
Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks
author_sort Chia-Ming Hsu
title Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks
title_short Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks
title_full Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks
title_fullStr Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks
title_full_unstemmed Mining Dense Overlapping Subgraphs in Weighted Protein-Protein Interaction Networks
title_sort mining dense overlapping subgraphs in weighted protein-protein interaction networks
publishDate 2007
url http://ndltd.ncl.edu.tw/handle/36566464250907433472
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