BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

334 related articles for article (PubMed ID: 29272335)

  • 41. A sparse PLS for variable selection when integrating omics data.
    Lê Cao KA; Rossouw D; Robert-Granié C; Besse P
    Stat Appl Genet Mol Biol; 2008; 7(1):Article 35. PubMed ID: 19049491
    [TBL] [Abstract][Full Text] [Related]  

  • 42. R/PY-SUMMA: An R/Python Package for Unsupervised Ensemble Learning for Binary Classification Problems in Bioinformatics.
    Ahsen ME; Vogel R; Stolovitzky GA
    J Comput Biol; 2020 Sep; 27(9):1337-1340. PubMed ID: 31905016
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Integration of multi-omics datasets enables molecular classification of COPD.
    Li CX; Wheelock CE; Sköld CM; Wheelock ÅM
    Eur Respir J; 2018 May; 51(5):. PubMed ID: 29545283
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Sliced inverse regression for integrative multi-omics data analysis.
    Jain Y; Ding S; Qiu J
    Stat Appl Genet Mol Biol; 2019 Jan; 18(1):. PubMed ID: 30685747
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Exploratory analysis of multiple omics datasets using the adjusted RV coefficient.
    Mayer CD; Lorent J; Horgan GW
    Stat Appl Genet Mol Biol; 2011; 10():Article 14. PubMed ID: 21381439
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Consistency and overfitting of multi-omics methods on experimental data.
    McCabe SD; Lin DY; Love MI
    Brief Bioinform; 2020 Jul; 21(4):1277-1284. PubMed ID: 31281919
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Robust clustering of noisy high-dimensional gene expression data for patients subtyping.
    Coretto P; Serra A; Tagliaferri R
    Bioinformatics; 2018 Dec; 34(23):4064-4072. PubMed ID: 29939219
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes.
    Kim S; Herazo-Maya JD; Kang DD; Juan-Guardela BM; Tedrow J; Martinez FJ; Sciurba FC; Tseng GC; Kaminski N
    BMC Genomics; 2015 Nov; 16():924. PubMed ID: 26560100
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Enter the Matrix: Factorization Uncovers Knowledge from Omics.
    Stein-O'Brien GL; Arora R; Culhane AC; Favorov AV; Garmire LX; Greene CS; Goff LA; Li Y; Ngom A; Ochs MF; Xu Y; Fertig EJ
    Trends Genet; 2018 Oct; 34(10):790-805. PubMed ID: 30143323
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Integrated enrichment analysis and pathway-centered visualization of metabolomics, proteomics, transcriptomics, and genomics data by using the InCroMAP software.
    Eichner J; Rosenbaum L; Wrzodek C; Häring HU; Zell A; Lehmann R
    J Chromatogr B Analyt Technol Biomed Life Sci; 2014 Sep; 966():77-82. PubMed ID: 24811976
    [TBL] [Abstract][Full Text] [Related]  

  • 51. HetEnc: a deep learning predictive model for multi-type biological dataset.
    Wu L; Liu X; Xu J
    BMC Genomics; 2019 Aug; 20(1):638. PubMed ID: 31395005
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Towards multi-omics synthetic data integration.
    Selvarajoo K; Maurer-Stroh S
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38711370
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.
    Tyler SR; Chun Y; Ribeiro VM; Grishina G; Grishin A; Hoffman GE; Do AN; Bunyavanich S
    Cell Rep; 2021 Apr; 35(2):108975. PubMed ID: 33852839
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Network-based drug discovery by integrating systems biology and computational technologies.
    Leung EL; Cao ZW; Jiang ZH; Zhou H; Liu L
    Brief Bioinform; 2013 Jul; 14(4):491-505. PubMed ID: 22877768
    [TBL] [Abstract][Full Text] [Related]  

  • 55. MCNF: A Novel Method for Cancer Subtyping by Integrating Multi-Omics and Clinical Data.
    Zhao L; Yan H
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(5):1682-1690. PubMed ID: 30990192
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Computational approaches for systems metabolomics.
    Krumsiek J; Bartel J; Theis FJ
    Curr Opin Biotechnol; 2016 Jun; 39():198-206. PubMed ID: 27135552
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Integration strategies of multi-omics data for machine learning analysis.
    Picard M; Scott-Boyer MP; Bodein A; Périn O; Droit A
    Comput Struct Biotechnol J; 2021; 19():3735-3746. PubMed ID: 34285775
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Unsupervised Multi-Omics Data Integration Methods: A Comprehensive Review.
    Vahabi N; Michailidis G
    Front Genet; 2022; 13():854752. PubMed ID: 35391796
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Integrative omics - from data to biology.
    Dihazi H; Asif AR; Beißbarth T; Bohrer R; Feussner K; Feussner I; Jahn O; Lenz C; Majcherczyk A; Schmidt B; Schmitt K; Urlaub H; Valerius O
    Expert Rev Proteomics; 2018 Jun; 15(6):463-466. PubMed ID: 29757692
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Multi-Input data ASsembly for joint Analysis (MIASA): A framework for the joint analysis of disjoint sets of variables.
    Raharinirina NA; Sunkara V; von Kleist M; Fackeldey K; Weber M
    PLoS One; 2024; 19(5):e0302425. PubMed ID: 38728301
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 17.