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 *

173 related articles for article (PubMed ID: 30400837)

  • 1. Bayesian variable selection for parametric survival model with applications to cancer omics data.
    Duan W; Zhang R; Zhao Y; Shen S; Wei Y; Chen F; Christiani DC
    Hum Genomics; 2018 Nov; 12(1):49. PubMed ID: 30400837
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Scalable Bayesian variable selection for structured high-dimensional data.
    Chang C; Kundu S; Long Q
    Biometrics; 2018 Dec; 74(4):1372-1382. PubMed ID: 29738602
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.
    Liu C; Wang X; Genchev GZ; Lu H
    Methods; 2017 Jul; 124():100-107. PubMed ID: 28627406
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data.
    Shen J; Wang S; Sun H; Huang J; Bai L; Wang X; Dong Y; Tang Z
    BMC Med Res Methodol; 2024 May; 24(1):105. PubMed ID: 38702624
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An Efficient Algorithm for the Detection of Outliers in Mislabeled Omics Data.
    Sun H; Wang J; Zhang Z; Hu N; Wang T
    Comput Math Methods Med; 2021; 2021():9436582. PubMed ID: 34976114
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A fast algorithm for Bayesian multi-locus model in genome-wide association studies.
    Duan W; Zhao Y; Wei Y; Yang S; Bai J; Shen S; Du M; Huang L; Hu Z; Chen F
    Mol Genet Genomics; 2017 Aug; 292(4):923-934. PubMed ID: 28534238
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer.
    Kim D; Li R; Dudek SM; Ritchie MD
    J Biomed Inform; 2015 Aug; 56():220-8. PubMed ID: 26048077
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Bi-EB: Empirical Bayesian Biclustering for Multi-Omics Data Integration Pattern Identification among Species.
    Yazdanparast A; Li L; Zhang C; Cheng L
    Genes (Basel); 2022 Oct; 13(11):. PubMed ID: 36360219
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Hybrid L
    Huang HH; Liang Y
    Comput Methods Programs Biomed; 2018 Oct; 164():65-73. PubMed ID: 30195432
    [TBL] [Abstract][Full Text] [Related]  

  • 10. miRNA-target gene regulatory networks: A Bayesian integrative approach to biomarker selection with application to kidney cancer.
    Chekouo T; Stingo FC; Doecke JD; Do KA
    Biometrics; 2015 Jun; 71(2):428-38. PubMed ID: 25639276
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Bayesian multiple quantitative trait loci mapping for complex traits using markers of the entire genome.
    Huang H; Eversley CD; Threadgill DW; Zou F
    Genetics; 2007 Aug; 176(4):2529-40. PubMed ID: 17483433
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Iterative sure independence screening EM-Bayesian LASSO algorithm for multi-locus genome-wide association studies.
    Tamba CL; Ni YL; Zhang YM
    PLoS Comput Biol; 2017 Jan; 13(1):e1005357. PubMed ID: 28141824
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Genome-wide prediction using Bayesian additive regression trees.
    Waldmann P
    Genet Sel Evol; 2016 Jun; 48(1):42. PubMed ID: 27286957
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.
    Tang Z; Shen Y; Zhang X; Yi N
    Genetics; 2017 Jan; 205(1):77-88. PubMed ID: 27799277
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework.
    Yang H; Wei Q; Zhong X; Yang H; Li B
    Bioinformatics; 2017 Feb; 33(4):483-490. PubMed ID: 27797769
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Weibull regression with Bayesian variable selection to identify prognostic tumour markers of breast cancer survival.
    Newcombe PJ; Raza Ali H; Blows FM; Provenzano E; Pharoah PD; Caldas C; Richardson S
    Stat Methods Med Res; 2017 Feb; 26(1):414-436. PubMed ID: 25193065
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The Application of Bayesian Methods in Cancer Prognosis and Prediction.
    Chu J; Sun NA; Hu W; Chen X; Yi N; Shen Y
    Cancer Genomics Proteomics; 2022; 19(1):1-11. PubMed ID: 34949654
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Hierarchical Bayesian formulations for selecting variables in regression models.
    Rockova V; Lesaffre E; Luime J; Löwenberg B
    Stat Med; 2012 May; 31(11-12):1221-37. PubMed ID: 22275239
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Bayesian Variable Selection in Multilevel Item Response Theory Models with Application in Genomics.
    Fragoso TM; de Andrade M; Pereira AC; Rosa GJ; Soler JM
    Genet Epidemiol; 2016 Apr; 40(3):253-63. PubMed ID: 27027518
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Latent variable sdelection in multidimensional item response theory models using the expectation model selection algorithm.
    Xu PF; Shang L; Zheng QZ; Shan N; Tang ML
    Br J Math Stat Psychol; 2022 May; 75(2):363-394. PubMed ID: 34918834
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.