These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

235 related articles for article (PubMed ID: 27153589)

  • 1. Inferring gene targets of drugs and chemical compounds from gene expression profiles.
    Noh H; Gunawan R
    Bioinformatics; 2016 Jul; 32(14):2120-7. PubMed ID: 27153589
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Optimal design of gene knockout experiments for gene regulatory network inference.
    Ud-Dean SM; Gunawan R
    Bioinformatics; 2016 Mar; 32(6):875-83. PubMed ID: 26568633
    [TBL] [Abstract][Full Text] [Related]  

  • 3. TRaCE+: Ensemble inference of gene regulatory networks from transcriptional expression profiles of gene knock-out experiments.
    Ud-Dean SM; Heise S; Klamt S; Gunawan R
    BMC Bioinformatics; 2016 Jun; 17():252. PubMed ID: 27342648
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DeltaNeTS+: elucidating the mechanism of drugs and diseases using gene expression and transcriptional regulatory networks.
    Noh H; Hua Z; Chrysinas P; Shoemaker JE; Gunawan R
    BMC Bioinformatics; 2021 Mar; 22(1):108. PubMed ID: 33663384
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SIN-KNO: A method of gene regulatory network inference using single-cell transcription and gene knockout data.
    Wang H; Lian Y; Li C; Ma Y; Yan Z; Dong C
    J Bioinform Comput Biol; 2019 Dec; 17(6):1950035. PubMed ID: 32019417
    [TBL] [Abstract][Full Text] [Related]  

  • 6. SINCERITIES: inferring gene regulatory networks from time-stamped single cell transcriptional expression profiles.
    Papili Gao N; Ud-Dean SMM; Gandrillon O; Gunawan R
    Bioinformatics; 2018 Jan; 34(2):258-266. PubMed ID: 28968704
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Sparse Reconstruction Approach for Identifying Gene Regulatory Networks Using Steady-State Experiment Data.
    Zhang W; Zhou T
    PLoS One; 2015; 10(7):e0130979. PubMed ID: 26207991
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Inferring Gene Regulatory Networks in the Arabidopsis Root Using a Dynamic Bayesian Network Approach.
    de Luis Balaguer MA; Sozzani R
    Methods Mol Biol; 2017; 1629():331-348. PubMed ID: 28623595
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting gene targets of perturbations via network-based filtering of mRNA expression compendia.
    Cosgrove EJ; Zhou Y; Gardner TS; Kolaczyk ED
    Bioinformatics; 2008 Nov; 24(21):2482-90. PubMed ID: 18779235
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Reverse engineering gene regulatory networks: coupling an optimization algorithm with a parameter identification technique.
    Hsiao YT; Lee WP
    BMC Bioinformatics; 2014; 15 Suppl 15(Suppl 15):S8. PubMed ID: 25474560
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Inferring gene regulatory networks by integrating ChIP-seq/chip and transcriptome data via LASSO-type regularization methods.
    Qin J; Hu Y; Xu F; Yalamanchili HK; Wang J
    Methods; 2014 Jun; 67(3):294-303. PubMed ID: 24650566
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information.
    Zhang X; Zhao XM; He K; Lu L; Cao Y; Liu J; Hao JK; Liu ZP; Chen L
    Bioinformatics; 2012 Jan; 28(1):98-104. PubMed ID: 22088843
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.
    Liu LZ; Wu FX; Zhang WJ
    BMC Syst Biol; 2014; 8 Suppl 3(Suppl 3):S1. PubMed ID: 25350697
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Netter: re-ranking gene network inference predictions using structural network properties.
    Ruyssinck J; Demeester P; Dhaene T; Saeys Y
    BMC Bioinformatics; 2016 Feb; 17():76. PubMed ID: 26862054
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genetic network inference as a series of discrimination tasks.
    Kimura S; Nakayama S; Hatakeyama M
    Bioinformatics; 2009 Apr; 25(7):918-25. PubMed ID: 19189976
    [TBL] [Abstract][Full Text] [Related]  

  • 16. PoLoBag: Polynomial Lasso Bagging for signed gene regulatory network inference from expression data.
    Ghosh Roy G; Geard N; Verspoor K; He S
    Bioinformatics; 2021 Jan; 36(21):5187-5193. PubMed ID: 32697830
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Developmental gene regulatory network connections predicted by machine learning from gene expression data alone.
    Zhang J; Ibrahim F; Najmulski E; Katholos G; Altarawy D; Heath LS; Tulin SL
    PLoS One; 2021; 16(12):e0261926. PubMed ID: 34962963
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Extreme learning machines for reverse engineering of gene regulatory networks from expression time series.
    Rubiolo M; Milone DH; Stegmayer G
    Bioinformatics; 2018 Apr; 34(7):1253-1260. PubMed ID: 29182723
    [TBL] [Abstract][Full Text] [Related]  

  • 19. TIGRESS: Trustful Inference of Gene REgulation using Stability Selection.
    Haury AC; Mordelet F; Vera-Licona P; Vert JP
    BMC Syst Biol; 2012 Nov; 6():145. PubMed ID: 23173819
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Network perturbation analysis of gene transcriptional profiles reveals protein targets and mechanism of action of drugs and influenza A viral infection.
    Noh H; Shoemaker JE; Gunawan R
    Nucleic Acids Res; 2018 Apr; 46(6):e34. PubMed ID: 29325153
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.