BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

276 related articles for article (PubMed ID: 15951103)

  • 1. EXAMINE: a computational approach to reconstructing gene regulatory networks.
    Deng X; Geng H; Ali H
    Biosystems; 2005 Aug; 81(2):125-36. PubMed ID: 15951103
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A new multiple regression approach for the construction of genetic regulatory networks.
    Zhang SQ; Ching WK; Tsing NK; Leung HY; Guo D
    Artif Intell Med; 2010; 48(2-3):153-60. PubMed ID: 19963359
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Reconstruction of gene regulatory networks under the finite state linear model.
    Ruklisa D; Brazma A; Viksna J
    Genome Inform; 2005; 16(2):225-36. PubMed ID: 16901105
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Clustering short time series gene expression data.
    Ernst J; Nau GJ; Bar-Joseph Z
    Bioinformatics; 2005 Jun; 21 Suppl 1():i159-68. PubMed ID: 15961453
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Fast calculation of pairwise mutual information for gene regulatory network reconstruction.
    Qiu P; Gentles AJ; Plevritis SK
    Comput Methods Programs Biomed; 2009 May; 94(2):177-80. PubMed ID: 19167129
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Ensemble learning of genetic networks from time-series expression data.
    Nam D; Yoon SH; Kim JF
    Bioinformatics; 2007 Dec; 23(23):3225-31. PubMed ID: 17977884
    [TBL] [Abstract][Full Text] [Related]  

  • 7. H-CORE: enabling genome-scale Bayesian analysis of biological systems without prior knowledge.
    Jung S; Lee KH; Lee D
    Biosystems; 2007; 90(1):197-210. PubMed ID: 17005318
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Learning regulatory programs that accurately predict differential expression with MEDUSA.
    Kundaje A; Lianoglou S; Li X; Quigley D; Arias M; Wiggins CH; Zhang L; Leslie C
    Ann N Y Acad Sci; 2007 Dec; 1115():178-202. PubMed ID: 17934055
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A gene network simulator to assess reverse engineering algorithms.
    Di Camillo B; Toffolo G; Cobelli C
    Ann N Y Acad Sci; 2009 Mar; 1158():125-42. PubMed ID: 19348638
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Fitting a geometric graph to a protein-protein interaction network.
    Higham DJ; Rasajski M; Przulj N
    Bioinformatics; 2008 Apr; 24(8):1093-9. PubMed ID: 18344248
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Reverse-engineering transcriptional modules from gene expression data.
    Michoel T; De Smet R; Joshi A; Marchal K; Van de Peer Y
    Ann N Y Acad Sci; 2009 Mar; 1158():36-43. PubMed ID: 19348630
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks.
    Werhli AV; Grzegorczyk M; Husmeier D
    Bioinformatics; 2006 Oct; 22(20):2523-31. PubMed ID: 16844710
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparing association network algorithms for reverse engineering of large-scale gene regulatory networks: synthetic versus real data.
    Soranzo N; Bianconi G; Altafini C
    Bioinformatics; 2007 Jul; 23(13):1640-7. PubMed ID: 17485431
    [TBL] [Abstract][Full Text] [Related]  

  • 14. List-decoding methods for inferring polynomials in finite dynamical gene network models.
    Dingel J; Milenkovic O
    Bioinformatics; 2009 Jul; 25(13):1686-93. PubMed ID: 19401400
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Increasing feasibility of optimal gene network estimation.
    Hansen A; Ott S; Koentges G
    Genome Inform; 2004; 15(2):141-50. PubMed ID: 15706500
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Clustering microarray gene expression data using weighted Chinese restaurant process.
    Qin ZS
    Bioinformatics; 2006 Aug; 22(16):1988-97. PubMed ID: 16766561
    [TBL] [Abstract][Full Text] [Related]  

  • 17. New probabilistic graphical models for genetic regulatory networks studies.
    Wang J; Cheung LW; Delabie J
    J Biomed Inform; 2005 Dec; 38(6):443-55. PubMed ID: 15996532
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Inference of gene regulatory networks using S-system: a unified approach.
    Wang H; Qian L; Dougherty E
    IET Syst Biol; 2010 Mar; 4(2):145-56. PubMed ID: 20232994
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Stochastic dynamic modeling of short gene expression time-series data.
    Wang Z; Yang F; Ho DW; Swift S; Tucker A; Liu X
    IEEE Trans Nanobioscience; 2008 Mar; 7(1):44-55. PubMed ID: 18334455
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis data.
    Kim SY; Kim Y
    BMC Bioinformatics; 2006 Jul; 7():330. PubMed ID: 16817975
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.