全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于数据挖掘和网络分析的"脑心同治"分子机制研究

Keywords: 网络分析,数据挖掘,脑心同治,步长脑心通方,分子作用机制

Full-Text   Cite this paper   Add to My Lib

Abstract:

研究从分子层面出发,结合利用信息技术中的网络分析、聚类和关联规则分析方法,找到步长脑心通这一实现脑心同治的方剂中的化合物成分共同作用于人体内的主要靶标组合,并对比分析这些主要成分在基于冠心病和中风病相关的蛋白质交互作用网络中作用的节点的异同。结果从分子层面上找出该方的主要成分对于2种疾病频繁作用的共同靶标及对于2种疾病分别作用到的不同靶标,同时确定了主要成分在作用于2种疾病共同靶标的同时也间接影响到不同靶标,从而解释其脑心同治的分子作用机制。

References

[1]  Fred A L N, Leit?o J M N. Partitional vs hierarchical clustering using a minimum grammar complexity approach[J]. Advances in Pattern Recognition, 2000(1876): 193.
[2]  Agrawal R,Srikant R.Fast algorithms for mining association rules .San Jose: In Proceeding of the 20th International Conference on Very Large Databases, 1994:487.
[3]  Lusis A J, Fogelman A M, Fonarow G C. Genetic basis of atherosclerosis:Part I: new genes and pathways[J]. Circulation,2004,110:1868.
[4]  曹晓岚,韩宁.心脑同治学说的含义及临床应用[J].世界中西医结合杂志,2008,3(3): 129.
[5]  姚立枫.步长脑心通胶囊治疗中风恢复期43例临床疗效[J].天津药学,2010,22(4):31.
[6]  牛建昭,陈家旭.对异病同治内涵的思考[J].中医药学报,2003,31(4):1.
[7]  关静,李峰,宋月晗. "异病同治"的理论探讨[J].中国中医基础医学杂志,2006,12(9):650.
[8]  Yildirim M A, Goh K I ,Cusick M E, et al. Drug-target network[J]. Nat Biotechnol, 2007 , 25:1119.
[9]  Yamanishi Y, Araki M, Gutteridge A, et al. Prediction of drug-target interaction network from the integration of chemical and genomic spaces[J]. Bioinformatics,2008, 24:232.
[10]  Wu X, Jiang R, Zhang M Q, et al. Network-based global inference of human disease genes[J]. Mol Sys Biol,2008, 4:189.
[11]  Hopkins A L. Network pharmacology: the next paradigm in drug discovery[J]. Nat Chem Biol,2008, 4(11):682.
[12]  李梢.网络靶标:中药方剂网络药理学研究的-个切入点[J].中国中药杂志,2011,36(15):2017.
[13]  Stark C, Breitkreutz B J, Chatr-Aryamontri A, et al. The bioGRID interaction database:2011 update[J]. Nucleic Acids Res, 2011, 39(supp1): 698.
[14]  Kerrien S, Aranda B, Breuza L, et al .The IntAct molecular interaction database in 2012[J].Nucleic Acids Res, 2012, 40:841.
[15]  Keshava Prasad T S, Goel R, Kandasamy K, et al. Human protein reference database-2009 Update[J]. Nucleic Acids Res, 2009, 37: 767.
[16]  von Mering C, Jensen L J, Snel B, et al. STRING: known and predicted protein-protein associations, integrated and transferred across organisms[J]. Nucleic Acids Res,2005, 33:433.
[17]  Mostafavi S, Ray D, Warde-Farley D, et al. GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function[J]. Genome Biology,2008, 9(S1):4.
[18]  Hamosh A, Scott A F, Amberger J S, et al. Online mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders[J]. Nucleic Acids Res,2005, 33: 514.
[19]  Bruford E A, Lush M J, Wright M W, et al.The HGNC database in 2008: a resource for the human genome[J].Nucleic Acids Res,2008, 36:445.
[20]  Kanehisa M, Goto S, Furumichi M, et al. KEGG for representation and analysisof molecular networks involving diseases and drugs[J]. Nucleic Acids Res,2010, 38: 355.
[21]  Wang Y, Xiao J, Suzek T O, et al. PubChem: a public information system for analyzing bioactivities of small molecules[J]. Nucleic Acids Res,2009, 37:623.
[22]  Godden J W, Xue L, Bajorath J, et al. Combinatorial preferences affect molecular similarity/diversity calculations using binary fingerprints and tanimoto coefficients[J]. J Chem Inf Comput Sci,2000, 40(1):163.
[23]  Dantzig G B. On the shortest route through a network [J]. Management Sci,1960, 6(2):187.
[24]  Marques J P, Written Wu, Y F Trans. Pattern recognition concepts, methods and applications[M]. 2nd edition, Beijing: Tsinghua University Press, 2002:51.
[25]  朱文倩,朱发珍,王雯. 从中西医结合看心脑同治[J].世界中西医结合杂志,2011, 11: 61.
[26]  蔡广.步长脑心通的临床应用进展[J].山东医药,2007,47(34): 119.
[27]  娜孜古丽·斯依提,武霞. 步长脑心通胶囊治疗冠心病心绞痛临床观察[J].社区中医药,2012,12(25):149.
[28]  Kovacic S, Bakran M. Genetic susceptibility to atherosclerosis[J]. Stroke Res Treatment, 2012 (12): 5.
[29]  Alygina N A,Kostomarova I V,Vodolagina N N, et al. The genes of atherosclerosis and cardiovascular diseases [J]. Klin Med,2011, 89(3): 14.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133