期刊文献+

复杂疾病靶基因识别与网络重建的计算系统生物研究

COMPUTATIONAL SYSTEMS BIOLOGICAL RESEARCH ON IDENTIFYING TARGET GENES AND CONSTRUCTING NETWORKS FOR COMPLEX DISEASES
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摘要 复杂疾病相关靶基因的识别、构建疾病驱使相关基因网络及进行疾病机制研究,是功能基因组学研究中非常重要的科学问题。文章以计算系统生物学的观点和三维的角度,综述了基于生物谱(SNP遗传谱、芯片表达谱和2D-PAGE蛋白质谱等)的复杂疾病靶基因识别、多水平(SNPs虚拟网络、基因调控网络、蛋白质互作网络等)遗传网络逆向重构方法,及不同水平的网络之间在生物学和拓扑学上的纵向映射关系,并给出复杂疾病靶基因识别与网络关系的计算系统生物方法研究的未来展望。 Identifying target genes, constructing disease-driven gene networks for complex diseases and further research on pathogenesis are the key fields in the function genomics study. From computa- tional systems biological and three dimensional viewpoints, the authors carefully review on identifying tar-get genes based on biological profiles (SNP genetic profiles, gene expression profiles, 2D-PAGE protein profiles and so on) for complex diseases, reverse engineering genetic networks from multi-levels (SNPs dummy networks, gene regulatory networks, protein-protein interaction networks and so on) and portrait matching these heterogeneous networks from biology and topology. Furthermore, the authors also prospect the computational systems biological research on identification of target genes and construction of genetic networks for complex diseases.
出处 《生物物理学报》 CAS CSCD 北大核心 2007年第4期296-306,共11页 Acta Biophysica Sinica
基金 国家自然科学基金项目(30571034 30570424 30600367 30370798) 国家863项目(2007AA02Z329) 黑龙江科技攻关(GB03C602-4)~~
关键词 生物谱 基因识别 网络重建 纵向映射 计算系统生物 Biological profiles Gene mining Gene network reconstruction Portrait matching Com-putational systems biology
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参考文献81

  • 1Clare A,King RD.Machine learning of functional class from phenotype data.Bioinformatics,2002,18(1):160-166
  • 2Li LP,Weinberg CR,Darden TA,Pedersen LG.Gene selection for sample classification based on gene expression data:study of sensitivity to choice of parameters of the GA/KNN method.Bioinformatics,2001,17(12):1131-1142
  • 3DeRisi J,Penland L,Brown PO,Bittner ML,Meltzer PS,Ray M,Chen YD,Su YA,Trent JM.Use of a cDNA microarray to analyse gene expression patterns in human cancer.Nat Genet,1996,14(4):457-460
  • 4Soinov LA,Krestyaninova MA,Brazma A.Towards reconstruction of gene networks from expression data by supervised learning.Genome Biol,2003,4(1):R6
  • 5Hartemink AJ,Gifford DK,Jaakkola TS,Young RA.Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks.Pac Symp Biocomput,2001:422-433
  • 6Rison SC,Teichmann SA,Thornton JM.Homology,pathway distance and chromosomal localization of the small molecule metabolism enzymes in Escherichia coli.J Mol Biol,2002,318(3):911-932
  • 7Graff JC,Behnke M,Radke J,White M,Jutila MA.A comprehensive SAGE database for the analysis of gammadelta T cells.Int lmmunol,2006,18(4):613-626
  • 8Ma XH,Hu SJ,Ni H,Zhao YC,Tian Z,Liu JL,Ren G,Liang XH,Yu H,Wan P,Yang ZM.Serial analysis of gene expression in mouse uterus at the implantation site.J Biol Chem,2006,281(14):9351-9360
  • 9Noble D.Modeling the heart--from genes to cells to the whole organ.Science,2002,295(5560):1678-1682
  • 10Wishart MJ,Groblewski G,Goke BJ,Wagner AC,Williams JA.Secretagogue regulation of pancreatic acinar cell protein phosphorylation shown by large-scale 2D-PAGE.Am J Physiol,1994,267(4 Pt 1):G676-686

二级参考文献39

  • 1GOLUB T R, SLONIM D K, TAMAYO P, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring [ J ]. Science,1999, 286:531 - 537.
  • 2BURKE H B. Discovering patterns in microarray data[J]. Mol Diagn, 2000, 5:349-357.
  • 3MILLS J C, GORDON J I. A new approach for filtering noise from high - density oligonucleotide microarray datasets[ J]. Nucleic Acids Res, 2001, 29 :E72 - 72.
  • 4KOHAVI R, JOHN G H. Wrappers for feature subset selection [ J ]. Artificial Intelligence, 1997, 97:273 - 324.
  • 5BREIMAN L. Random forests [ J ]. Machine Learning,2001, 45:5-32.
  • 6BREIMAN L. Bagging predictors [ J ]. Machine Learning, 1996, 24:123 - 140.
  • 7DIETTERICH T G. Ensemble Methods in Machine Learning[M]. New York: Springer Verlag, 2000. 1 -15.
  • 8GUO Z, LI X, RAO S. Analysis of Medical Data: An Introduction to Bioinformatics [ M ]. Harbin: Harbin Publisher, 2001.
  • 9ALON U, BARKAI N, NOTTERMAN D A, et al. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays[J]. Proc Natl Acad Sci U S A, 1999,96: 6745 - 6750.
  • 10KOWALSKI J, DENHARDT D T. Regulation of the mRNA for monocyte - derived neutrophil - activating peptide in differentiating HL60 promyelocytes [ J ]. Mol Cell Biol, 1989, 9:1946 - 1957.

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