分析蛋白質交互作用網路是瞭解細胞過程重要的基礎，近年來有許多用數學與圖形概念建立的細胞內路訊號傳遞模組，可提供生物資訊專家有效的控制和修改。巨噬細胞是人體內免疫反應中的防衛細胞，它的生物機制透過一系列的受體與蛋白質交互作用建立，為了建立一個完整的巨噬細胞訊號傳遞網路，除了需要龐大的時間外，也需要科學家繁複的進行生物體實驗。
本論文開發一個圖形化蛋白質交互作用追蹤系統 - PathTracker。先針對文獻擷取出巨噬細胞內所有的蛋白質交互作用資訊，並利用圖形介面輔助使用者從已知的生化路徑圖形中嘗試去追蹤出其中新的蛋白質交互作用證據。
在文獻處理方面，利用名稱辨識、詞性標記等文字探勘技術擷取出在巨噬細胞內描述蛋白質交互作用的句子，並藉此分析出有可能存在的新調控路徑。使用者可根據本系統從文獻內所找出的訊號傳遞路徑嘗試從KEGG 所提供的已知路徑中再連結出新的反應事件(路徑)。利用本系統，我們針對KEGG 中的“toll-like receptor pathway”和“JAK-STAT signaling pathway”進行比對。實驗結果顯示利用本系統所擷取出文章中的蛋白質交互作用資訊，可以有效地提供使用者追蹤訊號傳遞路徑之功能。在圖形顯示方面，利用Cytoscape web 可直接於瀏覽器觀看與操作的便利性，開發一個含有完整訊號傳遞路徑結果並可提供使用者直接進行編輯與修改完整的網路圖，以電腦閱讀與視覺化呈現取代人工閱讀標記，大幅減少閱讀巨噬細胞相關文獻所需耗費的時間。

The analysis of protein interaction networks is fundamental to the understanding of cellular processes. Recently, many of cellular signaling models are constructed as well as transformed to the mathematical or graphical models, its effect to control and revise for scientists in the field of bioinformatics.
Macrophage is one of defense cell in human body for immune response, and its detailed molecular mechanisms (pathway) were constructed by a series of receptors and protein interactions. To build a complete pathway for macrophage, it does not only spend much of time but also demand series of complicated experimental in vivo.
In this study, we propose an automatic information retrieval system for extracting information on macrophage protein-protein interaction from literature, named PathTracker. A user-friendly web interface was constructed for presenting and revising the network in time. The aim of PathTracker is to provide the effective evidence for exploring novel routes in the given macrophage pathway. The extractions of novel routes were treated as auxiliary information that provides a comprehensive exploration for new signal path. Here, we exemplify both of the given pathways, ‘toll-like receptor pathway’ and ‘JAK-STAT signaling pathway’ respectively. The result shows that several novel routes could be found among the experimental pathways, it points out our system is capable to extract novel interaction from the given pathway. In order to construct biological data in visualization, we introduced the Cytoscape web package as graphical interface for users to compile and revise graphical network. To our best knowledge, our proposed system is the first graphical application for exploring novel routes. It supplies a novel concept for exploring interaction between protein entities, and effectively save much time in read much literature for biomedical researchers.

[1] Z. Lu, "PubMed and beyond: a survey of web tools for searching biomedical literature," Database, vol. 2011, January 1, 2011.
[2] S. Gordon, "The macrophage: Past, present and future," European Journal of Immunology, vol. 37, pp. S9-S17, 2007.
[3] D. A. Hume, "The mononuclear phagocyte system," Current Opinion in Immunology, vol. 18, pp. 49-53, 2006.
[4] S. Raza, N. McDerment, P. Lacaze, K. Robertson, S. Watterson, Y. Chen, M. Chisholm, G. Eleftheriadis, S. Monk, M. O'Sullivan, A. Turnbull, D. Roy, A. Theocharidis, P. Ghazal, and T. Freeman, "Construction of a large scale integrated map of macrophage pathogen recognition and effector systems," BMC Systems Biology, vol. 4, p. 63, 2010.
[5] C. T. Lopes, M. Franz, F. Kazi, S. L. Donaldson, Q. Morris, and G. D. Bader, "Cytoscape Web: an interactive web-based network browser," Bioinformatics, July 23, 2010.
[6] Ext JS: http://www.sencha.com/
[7] PubMed: http://www.ncbi.nlm.nih.gov/pubmed/
[8] The Journal of Immunology: http://www.jimmunol.org/
[9] G. D. Bader, D. Betel, and C. W. V. Hogue, "BIND: the Biomolecular Interaction Network Database," Nucleic Acids Research, vol. 31, pp. 248-250, January 1, 2003.
[10] T. S. Keshava Prasad, R. Goel, K. Kandasamy, S. Keerthikumar, S. Kumar, S. Mathivanan, D. Telikicherla, R. Raju, B. Shafreen, A. Venugopal, L. Balakrishnan, A. Marimuthu, S. Banerjee, D. S. Somanathan, A. Sebastian, S. Rani, S. Ray, C. J. Harrys Kishore, S. Kanth, M. Ahmed, M. K. Kashyap, R. Mohmood, Y. L. Ramachandra, V. Krishna, B. A. Rahiman, S. Mohan, P. Ranganathan, S. Ramabadran, R. Chaerkady, and A. Pandey, "Human Protein Reference Database—2009 update," Nucleic Acids Research, vol. 37, pp. D767-D772, January 1, 2009.
[11] A. Ceol, A. Chatr Aryamontri, L. Licata, D. Peluso, L. Briganti, L. Perfetto, L. Castagnoli, and G. Cesareni, "MINT, the molecular interaction database: 2009 update," Nucleic Acids Research, vol. 38, pp. D532-D539, January 1, 2010.
[12] L. Salwinski, C. S. Miller, A. J. Smith, F. K. Pettit, J. U. Bowie, and D. Eisenberg, "The Database of Interacting Proteins: 2004 update," Nucleic Acids Research, vol. 32, pp. D449-D451, January 1, 2004.
[13] C. Stark, B.-J. Breitkreutz, A. Chatr-aryamontri, L. Boucher, R. Oughtred, M. S. Livstone, J. Nixon, K. Van Auken, X. Wang, X. Shi, T. Reguly, J. M. Rust, A. Winter, K. Dolinski, and M. Tyers, "The BioGRID Interaction Database: 2011 update," Nucleic Acids Research, vol. 39, pp. D698-D704, January 1, 2011.
[14] B. Aranda, P. Achuthan, Y. Alam-Faruque, I. Armean, A. Bridge, C. Derow, M. Feuermann, A. T. Ghanbarian, S. Kerrien, J. Khadake, J. Kerssemakers, C. Leroy, M. Menden, M. Michaut, L. Montecchi-Palazzi, S. N. Neuhauser, S. Orchard, V. Perreau, B. Roechert, K. van Eijk, and H. Hermjakob, "The IntAct molecular interaction database in 2010," Nucleic Acids Research, vol. 38, pp. D525-D531, January 1, 2010.
[15] D. Szklarczyk, A. Franceschini, M. Kuhn, M. Simonovic, A. Roth, P. Minguez, T. Doerks, M. Stark, J. Muller, P. Bork, L. J. Jensen, and C. v. Mering, "The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored," Nucleic Acids Research, vol. 39, pp. D561-D568, January 1, 2011.
[16] KEGG: http://www.genome.jp/kegg/
[17] T. U. Consortium, "The Universal Protein Resource (UniProt) in 2010," Nucleic Acids Research, vol. 38, pp. D142-D148, January 1, 2010.
[18] T. Ono, H. Hishigaki, A. Tanigami, and T. Takagi, "Automated extraction of information on protein–protein interactions from the biological literature," Bioinformatics, vol. 17, pp. 155-161, February 1, 2001.
[19] D. Hanisch, K. Fundel, H.-T. Mevissen, R. Zimmer, and J. Fluck, "ProMiner: rule-based protein and gene entity recognition," BMC Bioinformatics, vol. 6, p. S14, 2005.
[20] Y. Miyao, K. Sagae, R. Sætre, T. Matsuzaki, and J. i. Tsujii, "Evaluating contributions of natural language parsers to protein–protein interaction extraction," Bioinformatics, vol. 25, pp. 394-400, February 1, 2009.
[21] Biopax: http://www.biopax.org/
[22] SBML: http://sbml.org/
[23] A. C. Villéger, S. R. Pettifer, and D. B. Kell, "Arcadia: a visualization tool for metabolic pathways," Bioinformatics, vol. 26, pp. 1470-1471, June 1, 2010.
[24] O. Babur, U. Dogrusoz, E. Demir, and C. Sander, "ChiBE: interactive visualization and manipulation of BioPAX pathway models," Bioinformatics, December 9, 2009.
[25] A. Dilek, M. E. Belviranli, and U. Dogrusoz, "VISIBIOweb: visualization and layout services for BioPAX pathway models," Nucleic Acids Research, vol. 38, pp. W150-W154, July 1, 2010.
[26] A. Barsky, J. L. Gardy, R. E. W. Hancock, and T. Munzner, "Cerebral: a Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation," Bioinformatics, vol. 23, pp. 1040-1042, April 15, 2007.
[27] A. Zinovyev, E. Viara, L. Calzone, and E. Barillot, "BiNoM: a Cytoscape plugin for manipulating and analyzing biological networks," Bioinformatics, vol. 24, pp. 876-877, March 15, 2008.
[28] J. von Eichborn, P. E. Bourne, and R. Preissner, "Cobweb: a Java applet for network exploration and visualisation," Bioinformatics, April 12, 2011.
[29] D. Warde-Farley, S. L. Donaldson, O. Comes, K. Zuberi, R. Badrawi, P. Chao, M. Franz, C. Grouios, F. Kazi, C. T. Lopes, A. Maitland, S. Mostafavi, J. Montojo, Q. Shao, G. Wright, G. D. Bader, and Q. Morris, "The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function," Nucleic Acids Research, vol. 38, pp. W214-W220, July 1, 2010.
[30] Ingenuity Pathway Analysis: http://www.ingenuity.com/
[31] M. Huang, X. Zhu, Y. Hao, D. G. Payan, K. Qu, and M. Li, "Discovering patterns to extract protein-protein interactions from full texts," Bioinformatics, July 29, 2004.
[32] K. Fundel, R. Küffner, and R. Zimmer, "RelEx—Relation extraction using dependency parse trees," Bioinformatics, vol. 23, pp. 365-371, February 1, 2007.
[33] Y. Niu, D. Otasek, and I. Jurisica, "Evaluation of linguistic features useful in extraction of interactions from PubMed; Application to annotating known, high-throughput and predicted interactions in I2D," Bioinformatics, vol. 26, pp. 111-119, January 1, 2010.
[34] A. Matsuzawa, K. Saegusa, T. Noguchi, C. Sadamitsu, H. Nishitoh, S. Nagai, S. Koyasu, K. Matsumoto, K. Takeda, and H. Ichijo, "ROS-dependent activation of the TRAF6-ASK1-p38 pathway is selectively required for TLR4-mediated innate immunity," Nat Immunol, vol. 6, pp. 587-592, 2005.
[35] A. Hishida, K. Matsuo, Y. Goto, Y. Mitsuda, A. Hiraki, M. Naito, K. Wakai, K. Tajima, and N. Hamajima, "Toll-Like Receptor 4 +3725 G/C Polymorphism, Helicobacter pylori Seropositivity, and the Risk of Gastric Atrophy and Gastric Cancer in Japanese," Helicobacter, vol. 14, pp. 47-53, 2009.
[36] M. T. H. Ng, R. van't Hof, J. C. Crockett, M. E. Hope, S. Berry, J. Thomson, M. H. McLean, K. E. L. McColl, E. M. El-Omar, and G. L. Hold, "Increase in NF-{kappa}B Binding Affinity of the Variant C Allele of the Toll-Like Receptor 9 -1237T/C Polymorphism Is Associated with Helicobacter pylori-Induced Gastric Disease," Infect. Immun., vol. 78, pp. 1345-1352, March 1, 2010.