BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

317 related articles for article (PubMed ID: 18586698)

  • 21. Dominant spectral component analysis for transcriptional regulations using microarray time-series data.
    Yeung LK; Szeto LK; Liew AW; Yan H
    Bioinformatics; 2004 Mar; 20(5):742-9. PubMed ID: 14751991
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Identification of context-specific gene regulatory networks with GEMULA--gene expression modeling using LAsso.
    Geeven G; van Kesteren RE; Smit AB; de Gunst MC
    Bioinformatics; 2012 Jan; 28(2):214-21. PubMed ID: 22106333
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Inferring genetic interactions via a nonlinear model and an optimization algorithm.
    Chen CM; Lee C; Chuang CL; Wang CC; Shieh GS
    BMC Syst Biol; 2010 Feb; 4():16. PubMed ID: 20184777
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Learning transcriptional networks from the integration of ChIP-chip and expression data in a non-parametric model.
    Youn A; Reiss DJ; Stuetzle W
    Bioinformatics; 2010 Aug; 26(15):1879-86. PubMed ID: 20525821
    [TBL] [Abstract][Full Text] [Related]  

  • 25. TF-Cluster: a pipeline for identifying functionally coordinated transcription factors via network decomposition of the shared coexpression connectivity matrix (SCCM).
    Nie J; Stewart R; Zhang H; Thomson JA; Ruan F; Cui X; Wei H
    BMC Syst Biol; 2011 Apr; 5():53. PubMed ID: 21496241
    [TBL] [Abstract][Full Text] [Related]  

  • 26. A Gibbs sampler for the identification of gene expression and network connectivity consistency.
    Brynildsen MP; Tran LM; Liao JC
    Bioinformatics; 2006 Dec; 22(24):3040-6. PubMed ID: 17060361
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Systematic identification of yeast cell cycle transcription factors using multiple data sources.
    Wu WS; Li WH
    BMC Bioinformatics; 2008 Dec; 9():522. PubMed ID: 19061501
    [TBL] [Abstract][Full Text] [Related]  

  • 28. An efficient algorithm to identify coordinately activated transcription factors.
    Hu H
    Genomics; 2010 Mar; 95(3):143-50. PubMed ID: 20060041
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Identifying cell cycle regulators and combinatorial interactions among transcription factors with microarray data and ChIP-chip data.
    Chen T; Li F
    Int J Bioinform Res Appl; 2009; 5(6):625-46. PubMed ID: 19887337
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Properly defining the targets of a transcription factor significantly improves the computational identification of cooperative transcription factor pairs in yeast.
    Wu WS; Lai FJ
    BMC Genomics; 2015; 16 Suppl 12(Suppl 12):S10. PubMed ID: 26679776
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Identifying cooperative transcription factors in yeast using multiple data sources.
    Lai FJ; Jhu MH; Chiu CC; Huang YM; Wu WS
    BMC Syst Biol; 2014; 8 Suppl 5(Suppl 5):S2. PubMed ID: 25559499
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data.
    Liu X; Jessen WJ; Sivaganesan S; Aronow BJ; Medvedovic M
    BMC Bioinformatics; 2007 Aug; 8():283. PubMed ID: 17683565
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Global and threshold-free Transcriptional Regulatory Networks reconstruction through integrating ChIP-Chip and expression data.
    Liu Q; Yang Y; Li Y; Zhang Z
    Curr Protein Pept Sci; 2011 Nov; 12(7):631-42. PubMed ID: 21827425
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Identifying combinatorial regulation of transcription factors and binding motifs.
    Kato M; Hata N; Banerjee N; Futcher B; Zhang MQ
    Genome Biol; 2004; 5(8):R56. PubMed ID: 15287978
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Yeast cell cycle transcription factors identification by variable selection criteria.
    Wang H; Wang YH; Wu WS
    Gene; 2011 Oct; 485(2):172-6. PubMed ID: 21703335
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Characterizing disease states from topological properties of transcriptional regulatory networks.
    Tuck DP; Kluger HM; Kluger Y
    BMC Bioinformatics; 2006 May; 7():236. PubMed ID: 16670008
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Iterative Modeling Reveals Evidence of Sequential Transcriptional Control Mechanisms.
    Cheng CS; Behar MS; Suryawanshi GW; Feldman KE; Spreafico R; Hoffmann A
    Cell Syst; 2017 Mar; 4(3):330-343.e5. PubMed ID: 28237795
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Finding regulatory modules through large-scale gene-expression data analysis.
    Kloster M; Tang C; Wingreen NS
    Bioinformatics; 2005 Apr; 21(7):1172-9. PubMed ID: 15513996
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Large-scale learning of combinatorial transcriptional dynamics from gene expression.
    Asif HM; Sanguinetti G
    Bioinformatics; 2011 May; 27(9):1277-83. PubMed ID: 21367870
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Transcription factor regulatory modules provide the molecular mechanisms for functional redundancy observed among transcription factors in yeast.
    Yang TH
    BMC Bioinformatics; 2019 Dec; 20(Suppl 23):630. PubMed ID: 31881824
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 16.