跳到主要內容

臺灣博碩士論文加值系統

(100.28.2.72) 您好!臺灣時間:2024/06/16 07:44
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:楊世匡
研究生(外文):Yang, Shih-Kuang
論文名稱:DynamicCross-TalkAnalysisamongTNF-R,TLR-4andIL-1RSignalingstoIKKinTNFα-inducedImmuneSystem
論文名稱(外文):免疫系統在TNFα刺激下TNF-R, TLR-4以及IL-1R傳遞至IKK信號途徑的動態交互作用分析
指導教授:陳博現
指導教授(外文):Chen, Bor-Sen
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:48
中文關鍵詞:免疫系統腫瘤壞死因子交互作用信號
外文關鍵詞:cross-talkTNFRTLR4IL1R
相關次數:
  • 被引用被引用:0
  • 點閱點閱:212
  • 評分評分:
  • 下載下載:25
  • 收藏至我的研究室書目清單書目收藏:0
Motivation
Development in systems biology can provide a global view to investigate numerous system properties of molecular networks. However there is still lack of systematic approaches to reconstruct the stochastic dynamic protein-protein association networks at different time stages via high-throughput data for further analysis of the possible cross-talks among different pathways.
Results
In this study we attempt to integrate protein-protein interactions from databases to construct the rough protein-protein association networks (PPAN) for immune systems. Further, the gene expression profiles of TNFα-induced HUVEC and a stochastic dynamic model are used to rebuild the significant PPANs at different time stage to illustrate the development of innate immune system. A new cross-talk ranking method is also suggested to evaluate the potential core elements in the related signaling pathways of Toll-like receptor 4 (TLR-4) as well as receptors for tumor necrosis factor (TNF-R) and interleukin-1 (IL-1R). The highly ranked cross-talks which are functionally relevant to the TNFα stress are also identified. A bow-tie structure is then extracted from these cross-talk pathways for the robustness of network structure, the coordination of signal transduction and feedback control for efficient immune responses to different stimuli, and several characteristics of signal transduction and feedback control in the infected organism are observed.
Conclusion
A systematic approach based on stochastic dynamic model is proposed for biologists to get more insight into the underlying defense mechanisms of immune systems via the construction of corresponding signaling networks upon specific stimulus. Apart from immune system, this systematic approach can also be applied to other signaling networks under different conditions for different species. As the experimental techniques for detecting protein expression levels advance enough and the microarray data with multiple sampling points are available in the future, the performance of the proposed method will be efficiently improved.
動機
系統生物學在近年來日益蓬勃發展,提供了研究學者們用全面性的觀點來探討許多生物系統的特性。然而在這門領域中,仍然缺乏一個系統化的方法去利用高產量的實驗數據重建不同時期之動態隨機蛋白質交互連結網路,以進行不同信號傳遞途徑之間的交互作用分析。
結果
在這篇研究當中,我們嘗試整合了由資料庫所得的蛋白質交互作用聯結來建構初步的蛋白質關聯性網路。接著我們利用一個隨機的動態模型結合受到促進腫瘤壞死因子刺激下的人體靜脈血管內皮細胞之基因表現量,來重建一個更具生物意義的蛋白質關聯性網路,並用它來描繪先天免疫系統在人體內作用的進程。在此,我們提出一個創新的信號傳遞交互作用分析方法,用來評估TNF-R, TLR-4以及IL-1R傳遞至IKK信號途徑中可能的核心蛋白質因子。在這些互相作用的信號傳遞途徑之中,我們發現了一個特殊的領結狀信號傳遞結構,這種結構有助於維持生物網路的強健性、信號傳遞的調節並根據不同的外來訊號刺激產生相對應的免疫反應。此外,許多訊號傳遞和回授控制的系統特性也在我們所建構的蛋白質關聯性網路中可以觀察到。
結論
本篇研究提供了一個根據隨機的動態模型來重建對特定刺激訊號之下的訊號傳遞網路,並幫助生物學家能夠對免疫系統潛在的防禦機制有更深一層的了解。除了免疫系統之外,這個方法亦能適用於不同物種、不同刺激之下的信號傳遞網路分析。當未來實驗技術的進步,可以讓我們偵測大範圍的蛋白質表現量以及獲得更多連續時間點的數據時,本篇所提出的方法將會具有更高的可靠度與真實性。
Contents
Abstract………………………………………………………………….i
Contents…………………………………………………………………ii
Chapter 1 Introduction………………………………………………1
Chapter 2 Rsults………………………………………………………5
2.1 Constructing the rough PPANs…………………………………5
2.2 Pruning the rough PPAN via a Dynamic Model………………6
2.3 Construction of refined PPANs at different stages of immune system.…………………………………………………………8
2.4 Topology of the refined PPANs………………………………9
2.5 Inspecting the TNFα signaling network……………………9
2.6 Inspecting the IL-1R and TLR-4 signaling networks……11
2.7 Cross-talk analysis of the refined PPANs…………………13
Chapter 3 Discussion…………………………………………………16
3.1 Dynamic progression of the PPANs……………………………16
3.2 Specific Architecture in the integrated signaling network…………………………………………………………………17
3.3 Possible existence of TLR4 endogenous ligand……………18
3.4 Negative feedback controls to the cross-talks…………19
Chapter 4 Conclusion…………………………………………………20
Chapter 5 Materials and Methods…………………………………22
5.1 Data selection.…………………………………………………22
5.2 Identification of the regulatory parameters……………22
5.3 Determination of significant interaction pairs…………23
5.4 Cross-talks analysis by counting the TRVs………………24
Bibliography……………………………………………………………26
Bibliography
1. Aggarwal BB: Signalling pathways of the TNF superfamily: a double-edged sword. Nature reviews 2003, 3(9):745-756.
2. Zhang S, Jin G, Zhang XS, Chen L: Discovering functions and revealing mechanisms at molecular level from biological networks. Proteomics 2007, 7(16):2856-2869.
3. Theilgaard-Monch K, Porse BT, Borregaard N: Systems biology of neutrophil differentiation and immune response. Current opinion in immunology 2006, 18(1):54-60.
4. Ichikawa JK, English SB, Wolfgang MC, Jackson R, Butte AJ, Lory S: Genome-wide analysis of host responses to the Pseudomonas aeruginosa type III secretion system yields synergistic effects. Cellular microbiology 2005, 7(11):1635-1646.
5. Girardin E, Grau GE, Dayer JM, Roux-Lombard P, Lambert PH: Tumor necrosis factor and interleukin-1 in the serum of children with severe infectious purpura. The New England journal of medicine 1988, 319(7):397-400.
6. Baglioni C: Mechanisms of cytotoxicity, cytolysis,and growth stimulation by TNF. In Tumor Necrosis Factors: The Molecules and Their Emerging Role in Medicine, ed. B Beutler, pp 425–38 New York: Raven 1992.
7. Felson DT, Anderson JJ, Boers M, Bombardier C, Furst D, Goldsmith C, Katz LM, Lightfoot R, Jr., Paulus H, Strand V et al: American College of Rheumatology. Preliminary definition of improvement in rheumatoid arthritis. Arthritis and rheumatism 1995, 38(6):727-735.
8. Clark IA: Along a TNF-paved road from dead parasites in red cells to cerebral malaria, and beyond. Parasitology 2009:1-12.
9. Berk BC, Abe JI, Min W, Surapisitchat J, Yan C: Endothelial atheroprotective and anti-inflammatory mechanisms. Annals of the New York Academy of Sciences 2001, 947:93-109; discussion 109-111.
10. Verstrepen L, Bekaert T, Chau TL, Tavernier J, Chariot A, Beyaert R: TLR-4, IL-1R and TNF-R signaling to NF-kappaB: variations on a common theme. Cell Mol Life Sci 2008, 65(19):2964-2978.
11. Li H, Lin X: Positive and negative signaling components involved in TNFalpha-induced NF-kappaB activation. Cytokine 2008, 41(1):1-8.
12. Brockman JA, Scherer DC, McKinsey TA, Hall SM, Qi X, Lee WY, Ballard DW: Coupling of a signal response domain in I kappa B alpha to multiple pathways for NF-kappa B activation. Molecular and cellular biology 1995, 15(5):2809-2818.
13. Werner SL, Barken D, Hoffmann A: Stimulus specificity of gene expression programs determined by temporal control of IKK activity. Science (New York, NY 2005, 309(5742):1857-1861.
14. Roberto Chignola MF, Diego Liberatie, Alessio Del Fabbro, Edoardo Milotti: Balance between cell survival and death: a minimal quantitative model of tumor necrosis factor alpha cytotoxicity. 2009.
15. Lipniacki T, Puszynski K, Paszek P, Brasier AR, Kimmel M: Single TNFalpha trimers mediating NF-kappaB activation: stochastic robustness of NF-kappaB signaling. BMC bioinformatics 2007, 8:376.
16. Kodama T: Time course gene expression of HUVEC after TNF-alpha treatment. NCBI GEO Database-GSE9055 2004.
17. Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M: KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic acids research 1999, 27(1):29-34.
18. CST: Cell Signaling Technology Pathway Database.
19. Keshava Prasad TS, Goel R, Kandasamy K, Keerthikumar S, Kumar S, Mathivanan S, Telikicherla D, Raju R, Shafreen B, Venugopal A et al: Human Protein Reference Database--2009 update. Nucleic acids research 2009, 37(Database issue):D767-772.
20. Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, Tyers M: BioGRID: a general repository for interaction datasets. Nucleic acids research 2006, 34(Database issue):D535-539.
21. Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, Doerks T, Julien P, Roth A, Simonovic M et al: STRING 8--a global view on proteins and their functional interactions in 630 organisms. Nucleic acids research 2009, 37(Database issue):D412-416.
22. Tracey KJ, Cerami A: Tumor necrosis factor: a pleiotropic cytokine and therapeutic target. Annual review of medicine 1994, 45:491-503.
23. Ji H, Pettit A, Ohmura K, Ortiz-Lopez A, Duchatelle V, Degott C, Gravallese E, Mathis D, Benoist C: Critical roles for interleukin 1 and tumor necrosis factor alpha in antibody-induced arthritis. The Journal of experimental medicine 2002, 196(1):77-85.
24. Chen NJ, Chio, II, Lin WJ, Duncan G, Chau H, Katz D, Huang HL, Pike KA, Hao Z, Su YW et al: Beyond tumor necrosis factor receptor: TRADD signaling in toll-like receptors. Proceedings of the National Academy of Sciences of the United States of America 2008, 105(34):12429-12434.
25. Lang T, Mansell A: The negative regulation of Toll-like receptor and associated pathways. Immunology and cell biology 2007, 85(6):425-434.
26. Ludwig A, Fechner M, Wilck N, Meiners S, Grimbo N, Baumann G, Stangl V, Stangl K: Potent anti-inflammatory effects of low-dose proteasome inhibition in the vascular system. Journal of molecular medicine (Berlin, Germany) 2009.
27. Alon U: An Introduction to System Biology. Chapman & Hall/Crc Mathematical and Computational Biology.
28. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research 2003, 13(11):2498-2504.
29. Watts DJ, Strogatz SH: Collective dynamics of 'small-world' networks. Nature 1998, 393(6684):440-442.
30. Barabasi AL, Albert R: Emergence of scaling in random networks. Science (New York, NY 1999, 286(5439):509-512.
31. Albert R: Scale-free networks in cell biology. Journal of cell science 2005, 118(Pt 21):4947-4957.
32. Hsu H, Shu HB, Pan MG, Goeddel DV: TRADD-TRAF2 and TRADD-FADD interactions define two distinct TNF receptor 1 signal transduction pathways. Cell 1996, 84(2):299-308.
33. Tada K, Okazaki T, Sakon S, Kobarai T, Kurosawa K, Yamaoka S, Hashimoto H, Mak TW, Yagita H, Okumura K et al: Critical roles of TRAF2 and TRAF5 in tumor necrosis factor-induced NF-kappa B activation and protection from cell death. The Journal of biological chemistry 2001, 276(39):36530-36534.
34. Yang J, Lin Y, Guo Z, Cheng J, Huang J, Deng L, Liao W, Chen Z, Liu Z, Su B: The essential role of MEKK3 in TNF-induced NF-kappaB activation. Nature immunology 2001, 2(7):620-624.
35. Blonska M, Shambharkar PB, Kobayashi M, Zhang D, Sakurai H, Su B, Lin X: TAK1 is recruited to the tumor necrosis factor-alpha (TNF-alpha) receptor 1 complex in a receptor-interacting protein (RIP)-dependent manner and cooperates with MEKK3 leading to NF-kappaB activation. The Journal of biological chemistry 2005, 280(52):43056-43063.
36. Ea CK, Deng L, Xia ZP, Pineda G, Chen ZJ: Activation of IKK by TNFalpha requires site-specific ubiquitination of RIP1 and polyubiquitin binding by NEMO. Molecular cell 2006, 22(2):245-257.
37. Hsu H, Huang J, Shu HB, Baichwal V, Goeddel DV: TNF-dependent recruitment of the protein kinase RIP to the TNF receptor-1 signaling complex. Immunity 1996, 4(4):387-396.
38. Wang C, Deng L, Hong M, Akkaraju GR, Inoue J, Chen ZJ: TAK1 is a ubiquitin-dependent kinase of MKK and IKK. Nature 2001, 412(6844):346-351.
39. Stylianou E, Saklatvala J: Interleukin-1. The international journal of biochemistry & cell biology 1998, 30(10):1075-1079.
40. Ye H, Arron JR, Lamothe B, Cirilli M, Kobayashi T, Shevde NK, Segal D, Dzivenu OK, Vologodskaia M, Yim M et al: Distinct molecular mechanism for initiating TRAF6 signalling. Nature 2002, 418(6896):443-447.
41. Takeda K, Akira S: TLR signaling pathways. Seminars in immunology 2004, 16(1):3-9.
42. Martin MU, Wesche H: Summary and comparison of the signaling mechanisms of the Toll/interleukin-1 receptor family. Biochimica et biophysica acta 2002, 1592(3):265-280.
43. Yamamoto M, Akira S: TIR domain-containing adaptors regulate TLR signaling pathways. Advances in experimental medicine and biology 2005, 560:1-9.
44. Medzhitov R, Preston-Hurlburt P, Kopp E, Stadlen A, Chen C, Ghosh S, Janeway CA, Jr.: MyD88 is an adaptor protein in the hToll/IL-1 receptor family signaling pathways. Molecular cell 1998, 2(2):253-258.
45. Greenfeder SA, Nunes P, Kwee L, Labow M, Chizzonite RA, Ju G: Molecular cloning and characterization of a second subunit of the interleukin 1 receptor complex. The Journal of biological chemistry 1995, 270(23):13757-13765.
46. Wesche H, Henzel WJ, Shillinglaw W, Li S, Cao Z: MyD88: an adapter that recruits IRAK to the IL-1 receptor complex. Immunity 1997, 7(6):837-847.
47. Zhang G, Ghosh S: Negative regulation of toll-like receptor-mediated signaling by Tollip. The Journal of biological chemistry 2002, 277(9):7059-7065.
48. Cheng H, Addona T, Keshishian H, Dahlstrand E, Lu C, Dorsch M, Li Z, Wang A, Ocain TD, Li P et al: Regulation of IRAK-4 kinase activity via autophosphorylation within its activation loop. Biochemical and biophysical research communications 2007, 352(3):609-616.
49. Li X, Commane M, Burns C, Vithalani K, Cao Z, Stark GR: Mutant cells that do not respond to interleukin-1 (IL-1) reveal a novel role for IL-1 receptor-associated kinase. Molecular and cellular biology 1999, 19(7):4643-4652.
50. Cao Z, Henzel WJ, Gao X: IRAK: a kinase associated with the interleukin-1 receptor. Science (New York, NY 1996, 271(5252):1128-1131.
51. Jiang Z, Ninomiya-Tsuji J, Qian Y, Matsumoto K, Li X: Interleukin-1 (IL-1) receptor-associated kinase-dependent IL-1-induced signaling complexes phosphorylate TAK1 and TAB2 at the plasma membrane and activate TAK1 in the cytosol. Molecular and cellular biology 2002, 22(20):7158-7167.
52. Lomaga MA, Yeh WC, Sarosi I, Duncan GS, Furlonger C, Ho A, Morony S, Capparelli C, Van G, Kaufman S et al: TRAF6 deficiency results in osteopetrosis and defective interleukin-1, CD40, and LPS signaling. Genes & development 1999, 13(8):1015-1024.
53. Sato S, Sanjo H, Takeda K, Ninomiya-Tsuji J, Yamamoto M, Kawai T, Matsumoto K, Takeuchi O, Akira S: Essential function for the kinase TAK1 in innate and adaptive immune responses. Nature immunology 2005, 6(11):1087-1095.
54. Gottipati S, Rao NL, Fung-Leung WP: IRAK1: a critical signaling mediator of innate immunity. Cellular signalling 2008, 20(2):269-276.
55. Thomas JA, Allen JL, Tsen M, Dubnicoff T, Danao J, Liao XC, Cao Z, Wasserman SA: Impaired cytokine signaling in mice lacking the IL-1 receptor-associated kinase. J Immunol 1999, 163(2):978-984.
56. Wu H, Arron JR: TRAF6, a molecular bridge spanning adaptive immunity, innate immunity and osteoimmunology. Bioessays 2003, 25(11):1096-1105.
57. Naito A, Azuma S, Tanaka S, Miyazaki T, Takaki S, Takatsu K, Nakao K, Nakamura K, Katsuki M, Yamamoto T et al: Severe osteopetrosis, defective interleukin-1 signalling and lymph node organogenesis in TRAF6-deficient mice. Genes Cells 1999, 4(6):353-362.
58. Bian ZM, Elner SG, Yoshida A, Kunkel SL, Su J, Elner VM: Activation of p38, ERK1/2 and NIK pathways is required for IL-1beta and TNF-alpha-induced chemokine expression in human retinal pigment epithelial cells. Experimental eye research 2001, 73(1):111-121.
59. Reiko Shinkura, Kazuhiro Kitada, Fumihiko Matsuda, Kei Tashiro, Koichi Ikuta, Misao Suzuki, Katsumi Kogishi, Serikawa T, Honjo T: Alymphoplasia is caused by a point mutation in the mouse gene encoding Nf-b-inducing kinase. 1999.
60. Nakano H, Oshima H, Chung W, Williams-Abbott L, Ware CF, Yagita H, Okumura K: TRAF5, an activator of NF-kappaB and putative signal transducer for the lymphotoxin-beta receptor. The Journal of biological chemistry 1996, 271(25):14661-14664.
61. Coornaert B, Carpentier I, Beyaert R: A20: central gatekeeper in inflammation and immunity. The Journal of biological chemistry 2009, 284(13):8217-8221.
62. Opipari AW, Jr., Hu HM, Yabkowitz R, Dixit VM: The A20 zinc finger protein protects cells from tumor necrosis factor cytotoxicity. The Journal of biological chemistry 1992, 267(18):12424-12427.
63. Lee EG, Boone DL, Chai S, Libby SL, Chien M, Lodolce JP, Ma A: Failure to regulate TNF-induced NF-kappaB and cell death responses in A20-deficient mice. Science (New York, NY 2000, 289(5488):2350-2354.
64. Yin L, Wu L, Wesche H, Arthur CD, White JM, Goeddel DV, Schreiber RD: Defective lymphotoxin-beta receptor-induced NF-kappaB transcriptional activity in NIK-deficient mice. Science (New York, NY 2001, 291(5511):2162-2165.
65. Yang J, Boerm M, McCarty M, Bucana C, Fidler IJ, Zhuang Y, Su B: Mekk3 is essential for early embryonic cardiovascular development. Nature genetics 2000, 24(3):309-313.
66. Oda K, Kitano H: A comprehensive map of the toll-like receptor signaling network. Molecular systems biology 2006, 2:2006 0015.
67. Turner NA, Mughal RS, Warburton P, O'Regan DJ, Ball SG, Porter KE: Mechanism of TNFalpha-induced IL-1alpha, IL-1beta and IL-6 expression in human cardiac fibroblasts: effects of statins and thiazolidinediones. Cardiovascular research 2007, 76(1):81-90.
68. Frantz S, Kobzik L, Kim YD, Fukazawa R, Medzhitov R, Lee RT, Kelly RA: Toll4 (TLR4) expression in cardiac myocytes in normal and failing myocardium. The Journal of clinical investigation 1999, 104(3):271-280.
69. Evans PC, Taylor ER, Coadwell J, Heyninck K, Beyaert R, Kilshaw PJ: Isolation and characterization of two novel A20-like proteins. The Biochemical journal 2001, 357(Pt 3):617-623.
70. Thomson W, Barton A, Ke X, Eyre S, Hinks A, Bowes J, Donn R, Symmons D, Hider S, Bruce IN et al: Rheumatoid arthritis association at 6q23. Nature genetics 2007, 39(12):1431-1433.
71. Musone SL, Taylor KE, Lu TT, Nititham J, Ferreira RC, Ortmann W, Shifrin N, Petri MA, Ilyas Kamboh M, Manzi S et al: Multiple polymorphisms in the TNFAIP3 region are independently associated with systemic lupus erythematosus. Nature genetics 2008.
72. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007, 447(7145):661-678.
73. Kalogeris TJ, Laroux FS, Cockrell A, Ichikawa H, Okayama N, Phifer TJ, Alexander JS, Grisham MB: Effect of selective proteasome inhibitors on TNF-induced activation of primary and transformed endothelial cells. The American journal of physiology 1999, 276(4 Pt 1):C856-864.
74. Dagia NM, Goetz DJ: A proteasome inhibitor reduces concurrent, sequential, and long-term IL-1 beta- and TNF-alpha-induced ECAM expression and adhesion. American journal of physiology 2003, 285(4):C813-822.
75. Cheong R, Bergmann A, Werner SL, Regal J, Hoffmann A, Levchenko A: Transient IkappaB kinase activity mediates temporal NF-kappaB dynamics in response to a wide range of tumor necrosis factor-alpha doses. The Journal of biological chemistry 2006, 281(5):2945-2950.
76. Akaike: A new look at the statistical model identification. Automatic Control,IEEE Transactions 1974, 19(6):716-723.
77. Johansson R: System modeling and identification. Englewood Cliffs, NJ rentice-Hall 1993.
78. Legler DF, Micheau O, Doucey MA, Tschopp J, Bron C: Recruitment of TNF receptor 1 to lipid rafts is essential for TNFalpha-mediated NF-kappaB activation. Immunity 2003, 18(5):655-664.
79. Blonska M, You Y, Geleziunas R, Lin X: Restoration of NF-kappaB activation by tumor necrosis factor alpha receptor complex-targeted MEKK3 in receptor-interacting protein-deficient cells. Molecular and cellular biology 2004, 24(24):10757-10765.
80. Lamothe B, Besse A, Campos AD, Webster WK, Wu H, Darnay BG: Site-specific Lys-63-linked tumor necrosis factor receptor-associated factor 6 auto-ubiquitination is a critical determinant of I kappa B kinase activation. The Journal of biological chemistry 2007, 282(6):4102-4112.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊
 
1. Investigating the Genome-wide Interspecies Genetic- and Epigenetic- Networks and the Molecular Mechanisms for Human B Lymphocytes Infected with Epstein-Barr Virus via Big Data Mining and Genome-wide Identification
2. 最佳化方法在通訊系統中之應用
3. 整合基因轉錄調控,蛋白質交互作用與細胞功能性之白色念珠菌感染宿主組織的細胞網路
4. RobustSensorimotorControlofHumanArmSystemunderState-dependentNoises,Control-dependentNoisesandAdditiveNoises
5. 以分解圖及外來資訊轉換曲線輔助的無線通訊系統之分析與設計
6. 通過系統生物學和深度學習方法研究老化過程機制並設計多分子藥物以緩解人體皮膚老化
7. 基於系統致癌機制和深度學習方法探討三陰性乳腺和非三陰性乳腺癌的系統藥物發現和設計
8. 藉由系統生物學方法建立基因與表觀遺傳網路來探究Caco-2細胞與困難梭狀桿菌於感染過程的訊號耦合機制
9. 再生與非再生基因調控網路之系統分析及再生醫學上之應用
10. 藉著比較幹細胞和癌細胞的基因和表觀遺傳因子的細胞週期調控網路來調查其中的癌化機制
11. 多種致癌的核心和特殊網路標記
12. 建構阿拉伯芥於光合作用的長期光適應行為下之基因調控網路
13. 適應性雙迴路分碼多重存取通訊系統中的多目標功率控制
14. 考慮多輸入多輸出正交分頻調變系統在快速時變的多通道下藉由模糊濾波器方法做強健性通道估測和等化器
15. 利用生物網路標記進行肺癌分子研究及診斷