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 *

185 related articles for article (PubMed ID: 38597610)

  • 1. NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders.
    Ruiz-Arenas C; Marín-Goñi I; Wang L; Ochoa I; Pérez-Jurado LA; Hernaez M
    Nucleic Acids Res; 2024 May; 52(9):e44. PubMed ID: 38597610
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Integrative analysis of survival-associated gene sets in breast cancer.
    Varn FS; Ung MH; Lou SK; Cheng C
    BMC Med Genomics; 2015 Mar; 8():11. PubMed ID: 25881247
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Shallow Sparsely-Connected Autoencoders for Gene Set Projection.
    Gold MP; LeNail A; Fraenkel E
    Pac Symp Biocomput; 2019; 24():374-385. PubMed ID: 30963076
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data.
    Srinivasan S; Leshchyk A; Johnson NT; Korkin D
    RNA; 2020 Oct; 26(10):1303-1319. PubMed ID: 32532794
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Assessment of gene set analysis methods based on microarray data.
    Alavi-Majd H; Khodakarim S; Zayeri F; Rezaei-Tavirani M; Tabatabaei SM; Heydarpour-Meymeh M
    Gene; 2014 Jan; 534(2):383-9. PubMed ID: 24012817
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Toward a gold standard for benchmarking gene set enrichment analysis.
    Geistlinger L; Csaba G; Santarelli M; Ramos M; Schiffer L; Turaga N; Law C; Davis S; Carey V; Morgan M; Zimmer R; Waldron L
    Brief Bioinform; 2021 Jan; 22(1):545-556. PubMed ID: 32026945
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A probabilistic approach for automated discovery of perturbed genes using expression data from microarray or RNA-Seq.
    Sundaramurthy G; Eghbalnia HR
    Comput Biol Med; 2015 Dec; 67():29-40. PubMed ID: 26492320
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Gene expression signatures of neuroendocrine prostate cancer and primary small cell prostatic carcinoma.
    Tsai HK; Lehrer J; Alshalalfa M; Erho N; Davicioni E; Lotan TL
    BMC Cancer; 2017 Nov; 17(1):759. PubMed ID: 29132337
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Increased comparability between RNA-Seq and microarray data by utilization of gene sets.
    van der Kloet FM; Buurmans J; Jonker MJ; Smilde AK; Westerhuis JA
    PLoS Comput Biol; 2020 Sep; 16(9):e1008295. PubMed ID: 32997685
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A flexible, interpretable, and accurate approach for imputing the expression of unmeasured genes.
    Mancuso CA; Canfield JL; Singla D; Krishnan A
    Nucleic Acids Res; 2020 Dec; 48(21):e125. PubMed ID: 33074331
    [TBL] [Abstract][Full Text] [Related]  

  • 11. GSVA: gene set variation analysis for microarray and RNA-seq data.
    Hänzelmann S; Castelo R; Guinney J
    BMC Bioinformatics; 2013 Jan; 14():7. PubMed ID: 23323831
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Graph Algorithms for Condensing and Consolidating Gene Set Analysis Results.
    Savage SR; Shi Z; Liao Y; Zhang B
    Mol Cell Proteomics; 2019 Aug; 18(8 suppl 1):S141-S152. PubMed ID: 31142576
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets.
    Park I; Lee KH; Lee D
    Bioinformatics; 2010 Jun; 26(12):1506-12. PubMed ID: 20410052
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An RNA-Seq-Based Framework for Characterizing Canine Prostate Cancer and Prioritizing Clinically Relevant Biomarker Candidate Genes.
    Thiemeyer H; Taher L; Schille JT; Packeiser EM; Harder LK; Hewicker-Trautwein M; Brenig B; Schütz E; Beck J; Nolte I; Murua Escobar H
    Int J Mol Sci; 2021 Oct; 22(21):. PubMed ID: 34768937
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Integration of RNA-Seq data with heterogeneous microarray data for breast cancer profiling.
    Castillo D; Gálvez JM; Herrera LJ; Román BS; Rojas F; Rojas I
    BMC Bioinformatics; 2017 Nov; 18(1):506. PubMed ID: 29157215
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis.
    Geddes TA; Kim T; Nan L; Burchfield JG; Yang JYH; Tao D; Yang P
    BMC Bioinformatics; 2019 Dec; 20(Suppl 19):660. PubMed ID: 31870278
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Assessment of Gene Set Enrichment Analysis using curated RNA-seq-based benchmarks.
    Candia J; Ferrucci L
    PLoS One; 2024; 19(5):e0302696. PubMed ID: 38753612
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data.
    Kinalis S; Nielsen FC; Winther O; Bagger FO
    BMC Bioinformatics; 2019 Jul; 20(1):379. PubMed ID: 31286861
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Interpretable and context-free deconvolution of multi-scale whole transcriptomic data with UniCell deconvolve.
    Charytonowicz D; Brody R; Sebra R
    Nat Commun; 2023 Mar; 14(1):1350. PubMed ID: 36906603
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Key pathways involved in prostate cancer based on gene set enrichment analysis and meta analysis.
    Ning QY; Wu JZ; Zang N; Liang J; Hu YL; Mo ZN
    Genet Mol Res; 2011 Dec; 10(4):3856-87. PubMed ID: 22194210
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.