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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 翁昭旼(Jau-Min Wong) | |
| dc.contributor.author | Chien-Chih Lin | en |
| dc.contributor.author | 林健智 | zh_TW |
| dc.date.accessioned | 2021-06-12T17:57:24Z | - |
| dc.date.available | 2016-08-26 | |
| dc.date.copyright | 2011-08-26 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-21 | |
| dc.identifier.citation | [1] Michael P. Cary, et al., 'Pathway information for systems biology', FEBS Letters, vol. 579, pp. 1815-1820, Feb 2005.
[2] Gary D. Bader, et al., 'Pathguide: a Pathway Resource List', Nucleic Acids Research, vol. 34, pp. D504-D506, Oct 2005. [3] Chris Stark, et al., 'BioGRID: a general repository for interaction datasets', Nucleic Acids Research, vol. 34, pp. D535-D539, Oct 2005. [4] Bobby-Joe Breitkreutz, et al., 'The BioGRID Interaction Database: 2008 update', Nucleic Acids Research, vol. 36, pp. D637-D640, Oct 2007. [5] Ioannis Xenarios, et al., 'DIP: the Database of Interacting Proteins', Nucleic Acids Research, vol. 28, pp. 289-291, Oct 1999. [6] Ioannis Xenarios, et al., 'DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions.', Nucleic Acids Research, vol. 30, pp. 303-305, Sep 2001. [7] Markus Krummenacker, et al., 'Querying and computing with BioCyc databases ', Bioinformatics, vol. 21, pp. 3454-3455, Jun 2005. [8] Peter D. Karp, et al., 'Expansion of the BioCyc collection of pathway/genome databases to 160 genomes', Nucleic Acids Research, vol. 33, pp. 6083-6089, Sep 2005. [9] Ron Caspi, et al., 'The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases', Nucleic Acids Research, vol. 36, pp. D623-D631, Oct 2007. [10] Ron Caspi, et al., 'The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases', Nucleic Acids Research, vol. 38, pp. D473-D479, Oct 2009. [11] Takai-Igarashi T, et al., 'A database for cell signaling networks.', Journal of Computational Biology, vol. 5, pp. 747-754, 1998. [12] Takai-Igarashi T, et al., 'A pathway finding system for the cell signaling networks database.', In Silico Biology, vol. ed, pp. 129-146, 1998. [13] Ran Elkon, et al., 'SPIKE--a database, visualization and analysis tool of cellular signaling pathways.', BMC Bioinformatics, vol. 9, pp. ed, 2008. [14] V. Matys, et al., 'TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes', Nucleic Acids Research, vol. 34, pp. D108-D110, 2005. [15] Wingender, Edgar, 'The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation.', BRIEFINGS IN BIOINFORMATICS, vol. 9, pp. 326-332, 2008. [16] Fang Zhao, et al., 'TRED: a Transcriptional Regulatory Element Database and a platform for in silico gene regulation studies', Nucleic Acids Research, vol. 33, pp. D103-D107, 2004. [17] C. Jiang, et al., 'TRED: a transcriptional regulatory element database , new entries and other development', Nucleic Acids Research, vol. 35, pp. D137-D140, 2006. [18] Minoru Kanehisa, et al., 'KEGG: Kyoto Encyclopedia of Genes and Genomes', in Pattern Recognition, Nucleic Acids Research, vol. 28, pp. 27-30, 2000. [19] Aoki Kinoshita, et al., 'Gene annotation and pathway mapping in KEGG', Methods in Molecular Biology, vol. ed, pp. 71-79, 2007. [20] KEGG http://www.genome.jp/kegg/ [21] Ekins, Sean, et al., 'Pathway mapping tools for analysis of high content data.', High Content Screening, vol. 356, pp. 319-350, 2007. [22] GeneGo MetaCore http://www.genego.com/ [23] Ulf Leser, et al., 'What makes a gene name? Named entity recognition in the biomedical literature', BRIEFINGS IN BIOINFORMATICS, vol. 6, pp. 357-369, 2005. [24] Frank Schacherer, et al., 'The TRANSPATH signal transduction database: a knowledge base on signal transduction networks' Bioinformatics, vol. 17, pp. 1053-1057, 2001. [25] J. C. Bezdek, et al., 'TRANSPATH : an information resource for storing and visualizing signaling pathways and their pathological aberrations', Nucleic Acids Research, vol. 34, pp. D546-D551, 2006. [26] Claudia Choi, et al., 'Consistent re-modeling of signaling pathways and its implementation in the TRANSPATH database', BIOBASE GmbH, vol. ed, pp. ed, 2004. [27] TRANSPATH Database http://www.gene-regulation.com/ [28] NCBI PubMed http://www.ncbi.nlm.nih.gov/pubmed/ [29] Baruch Awerbuch, et al., 'Distributed BFS Algorithms', IEEE, vol. ed, pp. 250-256, 1985. [30] E. W. Dijkstra, 'A Note on Two Problems in Connexion with Graphs', Numerische Mathematik, vol. ed, pp. 269-271, 1959. [31] John T. Moy, 'OSPF Anatomy of an Inernet Routing Protocol.', 1998. [32] Adobe Flex http://www.adobe.com/tw/products/flex/ [33] Alias-i LingPipe http://alias-i.com/lingpipe/ [34] Liu, Enqi, et al., 'Increased expression of vascular endothelial growth factor in kidney leads to progressive impairment of glomerular functions', Journal of the American Society of Nephrology, vol. 18, pp. 2094-2104, 2007. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/27185 | - |
| dc.description.abstract | 於系統生物學中，信息傳導路徑提供了大量重要資訊，並且說明了信號分子之間的交互作用關係。藉由多條相關信息傳導路徑，可再進一步組成一關聯網路架構圖，此網路關聯圖可提供全面且具體的架構，並可呈現各信息傳導路徑間的因果關係。如能即時、準確地提供生醫領域研究人員具體的網路關聯圖，將可幫助研究人員快速彙整大量相關資訊，並可讓研究人員從圖中迅速獲得具體觀念架構，如此將能節省研究人員大量時間，更可增加其研究效率，因此迅速且準確地提供關聯架構圖是非常重要的議題。
綜合以上之論點，本研究主要目的為提供生醫領域研究人員具體且完善的信息傳導路徑圖。本研究以BIOBASE TRANSPATH資料庫為資料來源依據，先應用廣度優先搜尋演算法(Breadth-First Search Algorithm)的概念建立出相關路徑的樹狀資料結構，再利用出現於相同路徑上的概念，將兩兩分子元素之路徑建構出(Pathways Construction)並且應用最短路徑演算法(Dijkstra's Algorithm)的概念找出最短路徑，最後利用Adobe Flex開發工具，提供找出之相關資訊視覺上的呈現，繪出相關網路關聯圖。本研究參考目前KEGG繪製的VEGF Signaling Pathway，並證實所繪出的網路關聯圖具有一定程度上的完整性與可用性，並能加以輔助研究人員於其相關研究之應用。 | zh_TW |
| dc.description.abstract | Signal transduction pathways provide a lot of important information in systems biology, which identify the functional relationships among molecular components, such as gene, gene product and protein. Furthermore, we can form the biological network by multiple pathways, which provide comprehensive concepts of biological process and reveals the complex causation. However, if we can provide researchers with related networks immediately, we can also assist them to retrieve knowledge effectively and obtain the concrete concept from the biological network. It will save researchers a lot of time and improve their efficiency. Therefore, to provide the biological network rapidly and properly is an important issue.
Based on the above arguments, the main purpose of this thesis is to provide researchers in the biomedical field with signal transduction pathways networks concretely and comprehensively. In this research, the data source comes from the BIOBASE TRANSPATH database. First of all, we apply Breadth-First Search algorithm to construct the tree data structure and we construct the pathway by the concept of two molecules in the same path. After constructing the pathways, we apply Dijkstra’s algorithm to find the shortest path, and finally Adobe Flex Development Tools is used to design visualization of the graphical user interface. This graphical user interface is used to integrate related information and provide visualization of biological networks. In this thesis, we compare the network of VEGF signaling pathway constructed by our methods to the network by KEGG, and we prove that the network constructed by our methods has a certain degree of integrity and usability. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-12T17:57:24Z (GMT). No. of bitstreams: 1 ntu-100-R98548054-1.pdf: 1385218 bytes, checksum: 5aa89fa9686bbf1ea32d2f2d300eb43c (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 誌謝 I
中文摘要 II Abstract III 目錄 V 圖目錄 VII 表目錄 VIII 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的 2 1.3 論文架構 3 第二章 相關研究 4 2.1 生物路徑資料庫相關研究 4 2.2 生物網路視覺化相關研究 7 2.3 命名實體識別相關研究 9 第三章 材料與方法 10 3.1 研究材料 10 3.1.1 BIOBASE TRANSPATH Database 10 3.1.2 PubMed Database 11 3.2 研究方法 12 3.2.1 廣度優先搜尋演算法 (Breadth-First Search, BFS) 14 3.2.2 最短路徑演算法 (Dijkstra's Algorithm) 15 3.2.3 路徑建構 (Pathways Construction) 17 3.2.4 視覺化方法 (Visualization) 19 3.2.5 命名實體識別 (Named Entity Recognition) 20 第四章 研究結果 21 4.1 Object Analysis Component 21 4.2 Shortest Path Search Component 24 4.3 Pathways Construction Component 25 4.4 PubMed Search Component 28 第五章 討論 31 5.1 Pathways Construction評估與討論 31 第六章 結論與未來展望 37 6.1 結論 37 6.2 未來展望 38 參考文獻 39 | |
| dc.language.iso | zh-TW | |
| dc.subject | 信息傳導路徑 | zh_TW |
| dc.subject | 視覺化 | zh_TW |
| dc.subject | 網路 | zh_TW |
| dc.subject | 廣度優先搜尋演算法 | zh_TW |
| dc.subject | 最短路徑演算法 | zh_TW |
| dc.subject | Signal Transduction Pathways | en |
| dc.subject | Breadth-First Search Algorithm | en |
| dc.subject | Network | en |
| dc.subject | Visualization | en |
| dc.title | 信息傳導路徑建構與視覺化呈現 | zh_TW |
| dc.title | Signal Transduction Pathways Construction and Visualization
by the TRANSPATH Database | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 蔣以仁(I-Jen Chiang) | |
| dc.contributor.oralexamcommittee | 陳中明 | |
| dc.subject.keyword | 信息傳導路徑,視覺化,網路,廣度優先搜尋演算法,最短路徑演算法, | zh_TW |
| dc.subject.keyword | Signal Transduction Pathways,Visualization,Network,Breadth-First Search Algorithm, | en |
| dc.relation.page | 41 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2011-08-22 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 醫學工程學研究所 | zh_TW |
| 顯示於系所單位： | 醫學工程學研究所 | |
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|---|---|---|---|
| ntu-100-1.pdf 未授權公開取用 | 1.35 MB | Adobe PDF |
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