BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

168 related articles for article (PubMed ID: 22691450)

  • 21. Regulatory interactions for iron homeostasis in Aspergillus fumigatus inferred by a Systems Biology approach.
    Linde J; Hortschansky P; Fazius E; Brakhage AA; Guthke R; Haas H
    BMC Syst Biol; 2012 Jan; 6():6. PubMed ID: 22260221
    [TBL] [Abstract][Full Text] [Related]  

  • 22. An improved Bayesian network method for reconstructing gene regulatory network based on candidate auto selection.
    Xing L; Guo M; Liu X; Wang C; Wang L; Zhang Y
    BMC Genomics; 2017 Nov; 18(Suppl 9):844. PubMed ID: 29219084
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks.
    White A; Vignes M
    Methods Mol Biol; 2019; 1883():111-142. PubMed ID: 30547398
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches.
    Cantone I; Marucci L; Iorio F; Ricci MA; Belcastro V; Bansal M; Santini S; di Bernardo M; di Bernardo D; Cosma MP
    Cell; 2009 Apr; 137(1):172-81. PubMed ID: 19327819
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Windowed Granger causal inference strategy improves discovery of gene regulatory networks.
    Finkle JD; Wu JJ; Bagheri N
    Proc Natl Acad Sci U S A; 2018 Feb; 115(9):2252-2257. PubMed ID: 29440433
    [TBL] [Abstract][Full Text] [Related]  

  • 26. TDSDMI: Inference of time-delayed gene regulatory network using S-system model with delayed mutual information.
    Yang B; Zhang W; Wang H; Song C; Chen Y
    Comput Biol Med; 2016 May; 72():218-25. PubMed ID: 27058285
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Learning the structure of gene regulatory networks from time series gene expression data.
    Li H; Wang N; Gong P; Perkins EJ; Zhang C
    BMC Genomics; 2011 Dec; 12 Suppl 5(Suppl 5):S13. PubMed ID: 22369588
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Comparing the reconstruction of regulatory pathways with distinct Bayesian networks inference methods.
    Werhli AV
    BMC Genomics; 2012; 13 Suppl 5(Suppl 5):S2. PubMed ID: 23095805
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Robust data-driven incorporation of prior knowledge into the inference of dynamic regulatory networks.
    Greenfield A; Hafemeister C; Bonneau R
    Bioinformatics; 2013 Apr; 29(8):1060-7. PubMed ID: 23525069
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.
    Park CY; Hess DC; Huttenhower C; Troyanskaya OG
    PLoS Comput Biol; 2010 Nov; 6(11):e1001009. PubMed ID: 21124865
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Bayesian inference based modelling for gene transcriptional dynamics by integrating multiple source of knowledge.
    Wang SQ; Li HX
    BMC Syst Biol; 2012; 6 Suppl 1(Suppl 1):S3. PubMed ID: 23046631
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A multiorganism based method for Bayesian gene network estimation.
    Dawy Z; Yaacoub E; Nassar M; Abdallah R; Zeineddine HA
    Biosystems; 2011 Mar; 103(3):425-34. PubMed ID: 21168470
    [TBL] [Abstract][Full Text] [Related]  

  • 33. IRIS: a method for reverse engineering of regulatory relations in gene networks.
    Morganella S; Zoppoli P; Ceccarelli M
    BMC Bioinformatics; 2009 Dec; 10():444. PubMed ID: 20030818
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Integrating transcriptional and protein interaction networks to prioritize condition-specific master regulators.
    Padi M; Quackenbush J
    BMC Syst Biol; 2015 Nov; 9():80. PubMed ID: 26576632
    [TBL] [Abstract][Full Text] [Related]  

  • 35. A hybrid Bayesian network learning method for constructing gene networks.
    Wang M; Chen Z; Cloutier S
    Comput Biol Chem; 2007 Oct; 31(5-6):361-72. PubMed ID: 17889617
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Modelling and Control of Gene Regulatory Networks for Perturbation Mitigation.
    Foo M; Kim J; Bates DG
    IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(2):583-595. PubMed ID: 29994499
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks.
    Imoto S; Higuchi T; Goto T; Tashiro K; Kuhara S; Miyano S
    Proc IEEE Comput Soc Bioinform Conf; 2003; 2():104-13. PubMed ID: 16452784
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Inference of regulatory networks with a convergence improved MCMC sampler.
    Agostinho NB; Machado KS; Werhli AV
    BMC Bioinformatics; 2015 Sep; 16():306. PubMed ID: 26399857
    [TBL] [Abstract][Full Text] [Related]  

  • 39. An approach for reduction of false predictions in reverse engineering of gene regulatory networks.
    Khan A; Saha G; Pal RK
    J Theor Biol; 2018 May; 445():9-30. PubMed ID: 29462626
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Supervised learning of gene-regulatory networks based on graph distance profiles of transcriptomics data.
    Razaghi-Moghadam Z; Nikoloski Z
    NPJ Syst Biol Appl; 2020 Jun; 6(1):21. PubMed ID: 32606380
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.