Modern bioinformatics meets traditional Chinese medicine

Briefings in Bioinformatics

Volumn 15, Issue 6, 2013, Pages 984-1003

  Gu, Peiqin ^a   Chen, Huajun ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Bioinformatics; Herbal synergism; Linked life data; Systems biology; Traditional chinese medicine

Indexed keywords

BIOLOGICAL MARKER; HERBACEOUS AGENT;

BIOLOGICAL ONTOLOGY; BIOLOGY; CHINESE MEDICINE; CULTURAL FACTOR; DRUG DATABASE; DRUG DEVELOPMENT; EVIDENCE BASED MEDICINE; GENETIC DATABASE; GENOMICS; HUMAN; INTEGRATIVE MEDICINE; METABOLISM; METABOLOMICS; PROCEDURES; PROTEOMICS; SYNDROME; SYSTEMS BIOLOGY;

BIOLOGICAL MARKERS; BIOLOGICAL ONTOLOGIES; COMPUTATIONAL BIOLOGY; CROSS-CULTURAL COMPARISON; DATABASES, GENETIC; DATABASES, PHARMACEUTICAL; DRUG DISCOVERY; DRUGS, CHINESE HERBAL; EVIDENCE-BASED MEDICINE; GENOMICS; HUMANS; INTEGRATIVE MEDICINE; MEDICINE, CHINESE TRADITIONAL; METABOLOMICS; PROTEOMICS; SYNDROME; SYSTEMS BIOLOGY;

EID: 84900329601     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbt063     Document Type: Article

References (119)

1. Xu J, Yang Y. Traditional Chinese medicine in the Chinese health care system. Health Policy 2009;90:133-9, 2009.
2. Cheung F. TCM: made in China. Nature 2011;480:S82-3.
3. Ridley RG. Medical need, scientific opportunity and the drive for antimalarial drugs. Nature 2002;415:686-93.
4. Tu Y. The discovery of artemisinin (qinghaosu) and gifts from Chinese medicine. NatMed 2011;17:1217-20.
5. Normile D. The New Face of Traditional Chinese Medicine. Science 2003;299:188-90.
6. Qiu J. China plans to modernize traditional medicine. Nature 2007;446:590-1.
7. Stone R. Lifting the veil on traditional Chinese medicine. Science 2008;319:709-10.
8. Jiang WY. Therapeutic wisdom in traditional Chinese medicine: a perspective from modern science. Trends Pharmacol Sci 2005;26:558-63.
9. Bell IR, Caspi O, Schwartz GER, et al. Integrative medicine and systemic outcomes research: issues in the emergence of a new model for primary health care. Arch InternMed 2002;162:133.
10. Zhang A, Sun H, Wang P, et al. Future perspectives of personalized medicine in traditional Chinese medicine: a systems biology approach. Complement Ther Med 2012;20: 93-9.
11. Hood L. Systems biology: integrating technology, biology, and computation. Mech Ageing Dev 2003;124:9-16.
12. Hood L, Heath JR, Phelps ME, et al. Systems biology and new technologies enable predictive and preventative medicine. Sci Signal 2004;306:640.
13. Cohen J. Bioinformatics-an introduction for computer scientists. ACMComput Surveys 2004;36:122-58.
14. Schäfer J, Strimmer K. An empirical Bayes approach to inferring large-scale gene association networks. Bioinformatics 2005;21:754-64.
15. Baldi P, Brunak S. Bionformatics: The Machine Learning Approach. The MIT Press, 2001.
16. Kitano H. Systems biology: a brief overview. Science 2002; 295:1662-64.
17. Ralt D. Intercellular communication, NO and the biology of Chinese medicine. Cell Commun Signal 2005;3:8.
18. Koo A, David N, Renato U, et al. In Silico Modeling of Shear-Stress-Induced Nitric Oxide Production in Endothelial Cells through Systems Biology. BiophysJ 2013; 104:2295-306.
19. Buriani A, Garcia-Bermejo ML, Bosisio E, etal. Omic techniques in systems biology approaches to traditional Chinese medicine research: present and future. J Ethnopharmacol 2012;140:535-44.
20. Mertz L. Creating Accurate Models of Life: merging biology and computer science. Pulse IEEE 2013;4:16-25.
21. Lockhart DJ, Winzeler EA. Genomics, gene expression and DNA arrays. Nature 2000;405:827-36.
22. Auffray C, Chen Z, Hood L. Systems medicine: the future of medical genomics and healthcare. GenomeMed 2009;1:2.
23. Fang YC, Huang HC, Chen HH, et al. TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining. BMC ComplementAlternativeMed 2008;8:58.
24. Wu Z, Zhou X, Liu B, et al. Text mining for finding functional community of related genes using TCM knowledge. In: Knowledge Discovery in Databases: PKDD 2004. Springer, 2004, 459-70.
25. Zhou X, Liu B, Wu Z, et al. Integrative mining of traditional Chinese medicine literature and MEDLINE for functional gene networks. Artif IntellMed 2007;41:87-104.
26. Zhao S, Li S. A co-module approach for elucidating drugdisease associations and revealing their molecular basis. Bioinformatics 2012;28:955-61.
27. Jiang M, Xiao C, Chen G, et al. Correlation between cold and hot pattern in traditional Chinese medicine and gene expression profiles in rheumatoid arthritis. FrontMed 2011;5: 219-28.
28. Youns M, Hoheisel JD, Efferth T. Toxicogenomics for the prediction of toxicity related to herbs from traditional Chinese medicine. PlantaMed 2010;76:2019.
29. Joyce AR, Palsson Bø. The model organism as a system: integrating 'omics' data sets. Nat RevMol Cell Biol 2006;7: 198-210.
30. Ayyadurai VAS. Service-Based Systems architecture for modeling the whole cell: a distributed collaborative engineering systems approach. FutVisions Biomed Bioinform 2011;1: 115-68.
31. Cho WC. Application of proteomics in Chinese medicine research. AmJChinMed 2007;35:911-22.
32. Guo P, Ma ZC, Li YF, et al. Effects of siwu tang on protein expression of bone marrow of blood deficiency mice induced by irradiation. China J Chin Material Med 2004;29: 893-6.
33. Su SB, Lu A, Li S, et al. Evidence-based ZHENG: a traditional Chinese medicine syndrome. Evidence-Based Complementary and Alternative Medicine. 2012, 2012.
34. Wang W, Zhao H, Chen J, et al. Bridge the gap between syndrome in Traditional Chinese Medicine and proteome in western medicine by unsupervised pattern discovery algorithm. In: IEEE International Conference on Networking, Sensing and Control, 2008 (ICNSC 2008). Hainan, China: IEEE. 2008, 745-50.
35. Hung YC, Wang PW, Pan TL. Functional proteomics reveal the effect of Salvia miltiorrhiza aqueous extract against vascular atherosclerotic lesions. Biochim Biophys Acta 2010; 1804:1310-21.
36. Kaddurah-Daouk R, Kristal BS, Weinshilboum RM. Metabolomics: a global biochemical approach to drug response and disease. Annu Rev Pharmacol Toxicol 2008;48: 653-83.
37. Zhang A, Sun H, Wang Z, et al. Metabolomics: towards understanding traditional Chinese medicine. Planta Med 2010;76:2026-35.
38. Wang M, Lamers RA, Korthout HA, et al. Metabolomics in the context of systems biology: bridging traditional Chinese medicine and molecular pharmacology. Phytotherapy Res 2005;19:173-82.
39. Lao YM, Jiang JG, Yan L. Application of metabolomics analytical techniques in the modernization and toxicology research of traditional Chinese medicine. Br J Pharmacol 2009;157:1128-41.
40. Wang X, Sun H, Zhang A, et al. Potential role of metabolomics approaches in the area of traditional Chinese medicine: as pillars of the bridge between Chinese and Western medicine. J Pharmaceutical Biomed Anal 2011;55:859-68.
41. Wang X, Yang B, Sun H, et al. Pattern recognition approaches and computational systems tools for ultra performance liquid chromatography-mass spectrometrybased comprehensive metabolomics profiling and pathways analysis of biological data sets. Anal Chem 2011; 84:428-39.
42. Wang X, Wang H, Wang A, et al. Metabolomics study on the toxicity of aconite root and its processed products using ultraperformance liquid-chromatography/electrospray- ionization synapt high-definition mass spectrometry coupled with pattern recognition approach and ingenuity pathway analysis. J Proteome Res 2011;11: 1284-301.
43. Chan E, Tan M, Xin J, et al. Interactions between traditional Chinese medicines and Western Therapeutics. Curr OptionDrug Discov Dev 2010;13:50-65.
44. McEwen J, Cumming F. The quality and safety of traditional Chinese medicines. Aust Prescr 2003;26:130-1.
45. Sharma V, Sarkar IN. Bionformatics opportunities for identification and study of medicinal plants. Brief Bioinform 2013; 14:238-50.
46. Sanderson K. Databases aim to bridge the East-West divide of drug discovery. NatMed 2011;17:1531.
47. Li DC, Zhong XK, Zeng ZP, et al. Application of targeted drug delivery system in Chinese medicine. J Controlled Release 2009;138:103-12.
48. Chen CY. TCM Database Taiwan: the world's largest traditional Chinese medicine database for drug screening in silico. Plos One 2011;6:e15939.
49. Feng Y, Wu Z, Chen H, et al. Data quality in traditional Chinese Medicine. In: International Conference on BioMedical Engineering and Informatics 2008 (BMEI 2008), Vol. 1. Hainan, China: IEEE, 2008, 255-9.
50. Chen H, Mao Y, Zheng X, et al. Towards Semantic e-Science for traditional Chinese medicine. BMC Bioinformatics 2007;8(Suppl 3):S6.
51. Li S, Zhang B, Jiang D, et al. Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae. BMC Bioinformatics 2010;11(Suppl 11):S6.
52. Ming Y, Lijing J, Peiqi C, et al. Complex systems entropy network and its application in data mining for ChineseMedicine Tumor Clinics. World Sci Technol 2012;14: 1376-84.
53. Chen G, Lu AP. Predicition of the mechanisms of salvia miltiorrhiza against atherosclerosis using text mining and network-based analysis. J Algorithms ComputatTechnol 2011; 5:139-44.
54. Zheng G, Jiang M, He X, et al. Discrete derivative: a data slicing algorithm for exploration of sharing biological networks between rheumatoid arthritis and coronary heart disease. BioDataMining 2011;4:1-21.
55. Li S. Network systems underlying traditional Chinese medicine syndrome and herb formula. Curr Bioinform 2009;4: 188-96.
56. Ma XH, Zheng CJ, Han LY, et al. Synergistic therapeutic actions of herbal ingredients and their mechanisms from molecular interaction and network perspectives. Drug DiscovToday 2009;14:579-88.
57. Li S, Zhang B, Zhang N. Network target for screening synergistic drug combinations with application to traditional Chinese medicine. BMC Syst Biol 2011; 5(Suppl 1):S10.
58. Wang Y, Yu L, Zhang L, et al. A novel methodology for multicomponent drug design and its application in optimizing the combination of active components from Chinese medicinal formula Shenmai. Chem Biol Drug Design 2010; 75:318-24.
59. Cheng HM, Li CC, Chen CY, et al. Application of bioactivity database of Chinese herbal medicine on the therapeutic prediction, drug development, and safety evaluation. J Ethnopharmacol 2010;132:429-37.
60. Leung EL, Cao ZW, Jiang ZH, et al. Network-based drug discovery by integrating systems biology and computational technologies. Brief Bioinform 2013;14:491-505.
61. Ayyadurai VAS, Dewey CF,Jr. CytoSolve: a Scalable computational method for dynamic integration of multiple molecular pathway models. Cell Mol Bioeng 2011; 4:28-45.
62. AI-Lazikani B, Banerji U, Workman P. Combinatorial drug therapy for cancer in the post-genomic era. Nat Biotechnol 2012;30:679-92.
63. Zhao J, Jiang P, Zhang W. Molecular networks for the study of TCM pharmacology. Brief Bioinform 2010;11: 417-30.
64. Ung CY, Li H, Cao ZW, et al. Are herb-pairs of traditional Chinese medicine distinguishable from others? Pattern analysis and artificial intelligence classification study of traditionally defined herbal properties. J Ethnopharmacol 2007; 111:371-7.
65. Barlow DJ, Buriani A, Ehrman T, et al. In-silico studies in Chinese herbal medicines research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to data. J Ethnopharmacol 2012;140: 526-34.
66. Jorgensen WL. The many roles of computation in drug discovery. Science 2004;303:1813-8.
67. Sucher NJ. The application of Chinese medicine to novel drug discovery. Expert OpinionDrugDiscov 2013;8:21-34.
68. Butterweck V, Derendorf H. Herb-Drug interactions. PlantaMed 2012;78:1399-9.
69. Xu X. New concepts and approaches for drug discovery based on traditional Chinese medicine. Drug DiscovToday Technol 2006;3:247-53.
70. Ehrman TM, Barlow DJ, Hylands PJ. In silico search for multi-agent anti-inflammatories in Chinese herbs and formulas. BioorgMed Chem 2010;18:2204-18.
71. Yang H, Chen J, Tang S, et al. New drug R and D of Traditional Chinese Medicine: role of data mining approaches. J Biol Syst 2009;17:329-47.
72. Zhou X, Li Y, Chen X. Computational identification of bioactive natural products by structure activity relationship. JMolGraphModel 2010;29:38-45.
73. Cao C, Wang H, Sui Y. Knowledge modeling and acquisition of traditional Chinese herbal drugs and formulae from text. Artif IntellMed 2004;32:3-13.
74. Kang YJ. Herbogeneomics: from traditional Chinese medicine to novel therapeutics. Exp Biol Med 2008;233: 1059-65.
75. Sackett DL. Evidence-based medicine. In: Seminars in Perinatology, Vol. 21. WB Saunders: Elsevier, 1997, 3-5.
76. van der Greef J, van Wietmarschen H, Schroën J, et al. Systems biology-based diagnostic principles as pillars of the bridge between Chinese and Western medicine. PlantaMed 2010;76:2036.
77. Konkimalla VB, Efferth T. Evidence-based Chinese medicine for cancer therapy. J Ethnopharmacol 2008;116:207-10.
78. Graziose R, Lila MA, Raskin I. Merging traditional Chinese medicine with modern drug discovery technologies to find novel drugs and functional foods. Curr Drug DiscovTechnol 2010;7:2.
79. Lu A, Jiang M, Zhang C, et al. An integrative approach of linking traditional Chinese medicine pattern classification and biomedicine diagnosis. J Ethnopharmacol 2012;141: 549-56.
80. Li S, Zhang ZQ, Wu LJ, et al. Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine- immune network. Syst Biol, 2007;1:51-60.
81. Ma T, Tan T, Zhang H, et al. Bridging the gap between traditional Chinese medicine and systems biology: the connection of Cold Syndrome and NEI network. Mol Biosyst 2010;6:613-9.
82. Chen RQ, Wong CM, Cao KJ, et al. An evidence-based validation of traditional Chinese medicine syndromes. ComplementTherMed 2010;18:199-205.
83. Yu S, Guo Z, Guan T, et al. Combining ZHENG Theory and High-Throughput Expression Data to Predict New Effects of Chinese Herbal Formulae. Evid Based Complement AlternatMed 2012;2012:986427.
84. Ou B, Huang D, Hampsch-Woodill M, et al. When east meets west: the relationship between yin-yang and antioxidation- oxidation. FASEB J 2003;17:127-9.
85. Li Q, Zhao D, Bezard E. Traditional Chinese medicine for Parkinson's disease: a review of Chinese literature. Behav Pharmacol 2006;17:403-10.
86. Wang Y, Yu Z, Jiang Y, et al. Automatic symptom name normalization in clinical records of traditional Chinese medicine. BMC Bioinform 2010;11:40.
87. Wang M, Geng Z, Wang M, etal. Combination of network construction and cluster analysis and its application to traditional Chinese medicine. In: Advances in Neural Networks- ISNN2006. Chengdu, China: Springer, 2006;777-85.
88. Zhang NL, Yuan S, Chen T, et al. Latent tree models and diagnosis in traditional Chinese medicine. Artif Intell Med 2008;42:229-46.
89. Zhang NL, Yuan S, Chen T, et al. Statistical validation of traditional Chinese medicine theories. JAlternatComplement Med 2008;14:583-7.
90. Zhang YS. Mathematical reasoning of treatment principle based on 'Yin Yang Wu Xing' theory in Traditional Chinese Medicine. ChinMed 2011;2:6-15.
91. Jiang M, Lu C, Zhang C, et al. Syndrome differentiation in modern research of traditional Chinese medicine. J Ethnopharmacol 2012;140:634-42.
92. Lu C, Zha Q, Chang A, et al. Pattern differentiation in traditional Chinese medicine can help define specific indications for biomedical therapy in the treatment of rheumatoid arthritis. JAlternative ComplementMed 2009;15: 1021-5.
93. Li-Weber M. Targeting apoptosis pathways in cancer by Chinese medicine. Cancer Lett 2010.
94. Chen KC, Chen CY. Stroke prevention by traditional Chinese medicine? A genetic algorithm, support vector machine and molecular dynamics approach. Soft Matter 2011;7:4001-8.
95. Li L, Singh RG, Zheng G, etal. A methodology for semantic integration of metadata in bioinformatics data sources. In: Proceedings of the 43rd Annual Southeast Regional Conference, Vol. 1. Kennesaw, GA, USA: ACM, 2005, 131-6.
96. Antezana E, Kuiper M, Mironov V. Biological knowledge management: the emerging role of the Semantic Web technologies. Brief Bioinform 2009;10:392-407.
97. Lassila O, Swick RR. Resource Description Framework (RDF) model and syntax specification. W3C, 1998.
98. McGuinness DL, Van Harmelen F. OWL web ontology language overview. W3C 2012;10:1376-84.
99. Splendiani A, Burger A, Paschke A, et al. Biomedical semantics in the Semantic Web. J Biomed Semantics 2011; 2(Suppl 1):S1.
100. Belleau F, Nolin MA, Tourigny N, et al. Bio2RDF: towards a mashup to build bioinformatics knowledge systems. J Biomed Inform 2008;41:706-16.
101. Wang X, Gorlitsky R, Almeida JS. From XML to RDF: how semantic web technologies will change the design of 'omic' standards. Nat Biotechnol 2005;23:1099-103.
102. Ashburner M, Ball CA, Blake JA, et al. Gene Ontology: tool for the unification of biology. NatGenet 2000;25:25-9.
103. Bairoch A, Apweiler R, Wu CH, et al. The universal protein resource (Uniprot). NucleicAcidsRes 2005;33(suppl 1): D154-9.
104. Ye Y, Jiang Z, Diao X, et al. An ontology-based hierarchical semantic modeling approach to clinical pathway workflows. Comput BiolMed 2009;39:722-32.
105. Schriml LM, Arze C, Nadendla S, et al. Disease Ontology: a backbone for disease semantic integration. Nucleic Acids Res 2012;40:D940-6.
106. Wishart DS, Knox C, Guo AC, et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res 2008;36(suppl 1):D901-6.
107. Wild DJ, Ding Y, Sheth AP, et al. Systems chemical biology and the Semantic Web: what they mean for the future of drug discovery research. Drug DiscovToday 2011; 17:469-74.
108. Searls DB. Data integration: challenges for drug discovery. Nat RevDrug Discov 2005;4:45-58.
109. Stein LD. Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges. Nat Rev Genet 2011;9:678-88.
110. Rubin DL, Shah NH, Noy NF. Biomedical ontologies: a functional perspective. Brief Bioinform 2008;9:75-90.
111. Bodenreider O, Stevens R. Bio-ontologies: current trends and future directions. Brief Bioinform 2006;7:256-74.
112. Li S, Wu L, Zhang Z. Constructing biological networks through combined literature mining and microarray analysis: a LMMA approach. Bioinformatics 2006;22:2143-50.
113. Samwald N, Dumontier M, Zhao J, et al. Integrating findings of traditional medicine with modern pharmaceutical research: the potential role of linked open data. ChinMed 2010;5:43.
114. Chen B, Ding Y, Wild DJ. Assessing drug target associations using semantic linked data. PLosComputat Biol 2012; 8:21002574.
115. Cheung K, Chen H. Semantic Web for data harmonization in Chinese medicine. ChinMed 2010;5:2.
116. Ho YS, So KF, Chang RC. Drug discovery from Chinese medicine against neurodegeneration in Alzheimer's and vascular dementia. ChinMed 2011;6:15.
117. Dudley JT, Butte AJ. In silico research in the era of cloud computing. Nat Biotechnol 2010;28:1181.
118. Eberhart A, Hasse P, Oberle D, et al. Semantic technologies and cloud computing. In: Foundations for theWeb of Information and Services. Berlin: Springer, 2011, 239-51.
119. Parekh HS, Liu G, Wei MQ. A new dawn for the use of traditional Chinese medicine in cancer therapy. MolCancer 2009;8:21.