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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 歐陽彥正(Yen-Jen Oyang),阮雪芬(Hsueh-Fen Juan) | |
| dc.contributor.author | Chen-Ching Lin | en |
| dc.contributor.author | 林振慶 | zh_TW |
| dc.date.accessioned | 2021-06-17T00:21:46Z | - |
| dc.date.available | 2012-06-27 | |
| dc.date.copyright | 2012-06-27 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-06-14 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66099 | - |
| dc.description.abstract | 蛋白質交互作用網路可用來呈現細胞內分子間活動的基礎架構並且提供了解疾病可能機制的契機。信使核醣核酸的表現量以及微型核醣核酸的調控會影響蛋白質的量，進而影響蛋白質交互作用網路中的每筆交互作用。因此，我們結合蛋白質交互作用網路、信使核醣核酸的表現量以及微型核醣核酸的調控發展出一套整合型的分析方法，並利用這套方法去探討蛋白質交互作用網路中的動態模組性以及微型核醣核酸調控的特定蛋白質交互作用網路。
在分析動態模組性方面，藉由整合擴張型心肌病變病人的信使核醣核酸表現量與蛋白質交互作用的資料，我們發現在正常及疾病的樣本間有大量的交互作用發生重新連結的現象，這可能揭露了隱含於靜態交互作用網路中的動態資訊。我們更發現了兩個與心臟衰竭相關的功能性網路模組，而這兩個模組在正常及疾病樣本間的動態特性更進一步地提供了一個潛在的擴張型心肌病變的分子機制。 在微型核醣核酸方面，藉由整合微型核醣核酸的調控目標基因以及蛋白質交互作用網路，我們發展了一套方法來發掘出微型核醣核酸調控的交互作用網路以及預測它們在特定情況下的功能。另外，運用這個方法在胃癌的研究中也發現了幾個與癌症的發展有關的微型核醣核酸調控網路。進一步的分析更發現這些微型核醣核酸具有抑制胃癌腫瘤的可能性。其中，miR-148a更可以透過其調控目標去減少癌細胞的侵略、遷移以及附著的能力來降低癌細胞的增生及轉移。 在此我們提出了一個新方法去探索不同情況下蛋白質網路中的動態模組性及微型核醣核酸調控機制，也成功找到了和心臟衰竭高度相關的網路模組及具抑制胃癌腫瘤潛力的微型核醣核酸。最後，這些找到的網路模組及微型核醣核酸調控的蛋白質網路可能可以作為新的藥物標靶和提供治療心臟衰竭及胃癌的新方向。 | zh_TW |
| dc.description.abstract | Protein interaction networks can represent the backbone of molecular activity within cells and thus provide opportunities for understanding the mechanism of diseases. Through their influence on protein abundance, mRNA expression and microRNA regulation can affect the interaction dynamics within protein networks. Therefore, we developed an integrative analysis of protein interaction network by incorporating mRNA expression and microRNA regulation to reveal the dynamic modularity and microRNA-regulated networks in protein interaction networks.
For the dynamic modularity analysis, we integrated mRNA expression profiles of a cohort of dilated cardiomyopathy patients with protein-protein interactions and found a large amount of interaction rewiring between normal and disease samples. It might suggest that the condition-specific dynamic information hid among otherwise common static interactions. We identified two heart-failure related functional modules that significantly emerged from the protein interaction networks. Additionally, the dynamic change of these modules between normal and disease states further suggested a potential molecular model of dilated cardiomyopathy. For microRNA regulations, we integrated the information of microRNA expression, target mRNA expression, and target protein-protein interaction and developed an approach to reveal microRNA-regulated protein interaction networks and to determine their functional roles in specific biological conditions. Applying this approach to investigate gastric tumor samples revealed several microRNA-regulated networks which were enriched in functions related to cancer progression. Further analyses showed that these microRNAs could be potential tumor suppressors of gastric cancer. Among them, miR-148a decreased tumor proliferation and metastasis by reducing the invasiveness, migratory and adhesive activities of tumor cells through its targets. In conclusion, we proposed a novel framework to discover the dynamic modularity and microRNA regulation embedded in the protein interaction networks in different biological states. It successfully revealed network modules closely related to heart failure and potential tumor suppressor microRNAs involved in gastric cancer. The revealed molecular modules and microRNA-regulated networks might be able to be used as potential drug targets and provide new directions for heart failure and gastric cancer therapy. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T00:21:46Z (GMT). No. of bitstreams: 1 ntu-101-D96945017-1.pdf: 15944039 bytes, checksum: f7fc03c63ac997b7465f9a675c67e732 (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 摘要 iii Abstract iv Table of Contents vi List of Figures ix List of Tables xi Chapter 1 Introduction 1 1.1 Protein Interaction Network 1 1.2 Microarray Analysis 2 1.3 MicroRNA Regulation 2 1.4 Integrative Analyses of PIN 3 Chapter 2 Materials and Methods 7 2.1 Human Protein Interaction Network and MicroRNA Targets 7 2.2 MicroRNA and mRNA Expression Profiles 7 2.3 Integrative Analyses of PIN 8 2.3.1 Dynamic modularity of PIN 10 2.3.2 MicroRNA-regulated PIN 10 2.4 Methods in the Integrative Analysis of PIN 13 2.4.1 Network properties 13 2.4.2 Pearson correlation coefficient 14 2.4.3 Hypergeometric test 14 2.4.4 Co-expressed protein interaction network 15 2.4.5 Identification of condition-specific functional modules 15 2.4.6 Evaluation of classification accuracy 17 2.4.7 Expression variations of microRNA and mRNA 17 2.4.8 MicroRNA-regulated PIN identification 18 2.4.9 Activities of microRNA-regulated PIN 18 2.4.10 Investigation of the functional roles of microRNAs in PIN 19 Chapter 3 Results 20 3.1 The Integrative Analyses of PIN 20 3.2 Dynamic Modularity of PIN 21 3.2.1 Condition-specific CePIN 21 3.2.2 Highly interacting proteins in CePIN tend to be differentially expressed and function as SDEGs in DCM 22 3.2.3 Identification of two DCM-related functional modules 26 3.2.4 Dynamic features of DCM-related modules 29 3.2.5 Robustness of dynamic modularity revealed by integrative analysis 33 3.4 MicroRNA Regulation in PIN 41 3.4.1 Correlations between expression profiles of microRNAs and targets 41 3.4.2 MicroRNA-regulated PIN in gastric cancer 46 3.4.3 Predicting the potential regulating functions of microRNAs in PIN 49 3.4.4 miR-148a-regulated PIN and its potential functions in gastric cancer 50 3.4.5 miR-148a affects gastric cancer metastasis through its regulated PIN 53 Chapter 4 Discussion 54 Chapter 5 Conclusions 61 References 62 Appendix A - Experimental Validations of miR-148a Functions in Gastric Cancer 69 A.1 Invasion Assays using Boyden Chamber Assays 69 A.2 Wound Healing Assays 69 A.3 Cell Adhesion Assays 69 A.4 Cell Proliferation Assays 70 A.5 Luciferase Reporter Assays 70 Appendix B - Publication List 71 Appendix C - Selected Publications 72 | |
| dc.language.iso | en | |
| dc.subject | 微型核醣核酸調控網路 | zh_TW |
| dc.subject | 蛋白質交互作用網路 | zh_TW |
| dc.subject | 信使核醣核酸表現量 | zh_TW |
| dc.subject | 微型核醣核酸調控 | zh_TW |
| dc.subject | 整合型網路分析 | zh_TW |
| dc.subject | 動態模組特性 | zh_TW |
| dc.subject | dynamic modularity | en |
| dc.subject | mRNA expression profile | en |
| dc.subject | microRNA-regulated network | en |
| dc.subject | protein interaction network | en |
| dc.subject | integrative network analysis | en |
| dc.subject | microRNA regulation | en |
| dc.title | 蛋白質交互作用網路中的動態模組及調控 | zh_TW |
| dc.title | Dynamic Modularity and Regulation in Protein Interaction Networks | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.coadvisor | 黃宣誠(Hsuan-Cheng Huang) | |
| dc.contributor.oralexamcommittee | 李文雄(Wen-Hsiung Li),蔣榮先(Jung-Hsien Chiang),曾新穆(Vincent Shin-Mu Tseng),蔡懷寬(Huai-Kuang Tsai) | |
| dc.subject.keyword | 蛋白質交互作用網路,信使核醣核酸表現量,微型核醣核酸調控,整合型網路分析,動態模組特性,微型核醣核酸調控網路, | zh_TW |
| dc.subject.keyword | protein interaction network,mRNA expression profile,microRNA regulation,integrative network analysis,dynamic modularity,microRNA-regulated network, | en |
| dc.relation.page | 135 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-06-15 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
| 顯示於系所單位： | 生醫電子與資訊學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-101-1.pdf 未授權公開取用 | 15.57 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。