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 *

282 related articles for article (PubMed ID: 31790389)

  • 1. CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data.
    Kang K; Meng Q; Shats I; Umbach DM; Li M; Li Y; Li X; Li L
    PLoS Comput Biol; 2019 Dec; 15(12):e1007510. PubMed ID: 31790389
    [TBL] [Abstract][Full Text] [Related]  

  • 2. CDSeqR: fast complete deconvolution for gene expression data from bulk tissues.
    Kang K; Huang C; Li Y; Umbach DM; Li L
    BMC Bioinformatics; 2021 May; 22(1):262. PubMed ID: 34030626
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deconvolution from bulk gene expression by leveraging sample-wise and gene-wise similarities and single-cell RNA-Seq data.
    Wang C; Lin Y; Li S; Guan J
    BMC Genomics; 2024 Sep; 25(1):875. PubMed ID: 39294558
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Improved cell composition deconvolution method of bulk gene expression profiles to quantify subsets of immune cells.
    Chiu YJ; Hsieh YH; Huang YH
    BMC Med Genomics; 2019 Dec; 12(Suppl 8):169. PubMed ID: 31856824
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deblender: a semi-/unsupervised multi-operational computational method for complete deconvolution of expression data from heterogeneous samples.
    Dimitrakopoulou K; Wik E; Akslen LA; Jonassen I
    BMC Bioinformatics; 2018 Nov; 19(1):408. PubMed ID: 30404611
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Complete deconvolution of cellular mixtures based on linearity of transcriptional signatures.
    Zaitsev K; Bambouskova M; Swain A; Artyomov MN
    Nat Commun; 2019 May; 10(1):2209. PubMed ID: 31101809
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Heterogeneous pseudobulk simulation enables realistic benchmarking of cell-type deconvolution methods.
    Hu M; Chikina M
    Genome Biol; 2024 Jul; 25(1):169. PubMed ID: 38956606
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deconvolution of heterogeneous tumor samples using partial reference signals.
    Qin Y; Zhang W; Sun X; Nan S; Wei N; Wu HJ; Zheng X
    PLoS Comput Biol; 2020 Nov; 16(11):e1008452. PubMed ID: 33253170
    [TBL] [Abstract][Full Text] [Related]  

  • 9. HArmonized single-cell RNA-seq Cell type Assisted Deconvolution (HASCAD).
    Chiu YJ; Ni CE; Huang YH
    BMC Med Genomics; 2023 Oct; 16(Suppl 2):272. PubMed ID: 37907883
    [TBL] [Abstract][Full Text] [Related]  

  • 10. ChimeRScope: a novel alignment-free algorithm for fusion transcript prediction using paired-end RNA-Seq data.
    Li Y; Heavican TB; Vellichirammal NN; Iqbal J; Guda C
    Nucleic Acids Res; 2017 Jul; 45(13):e120. PubMed ID: 28472320
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.
    Zhang H; Lee CAA; Li Z; Garbe JR; Eide CR; Petegrosso R; Kuang R; Tolar J
    PLoS Comput Biol; 2018 Apr; 14(4):e1006053. PubMed ID: 29630593
    [TBL] [Abstract][Full Text] [Related]  

  • 12. GLDADec: marker-gene guided LDA modeling for bulk gene expression deconvolution.
    Azuma I; Mizuno T; Kusuhara H
    Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38982642
    [TBL] [Abstract][Full Text] [Related]  

  • 13. EnDecon: cell type deconvolution of spatially resolved transcriptomics data via ensemble learning.
    Tu JJ; Li HS; Yan H; Zhang XF
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36610709
    [TBL] [Abstract][Full Text] [Related]  

  • 14. CAM3.0: determining cell type composition and expression from bulk tissues with fully unsupervised deconvolution.
    Wu CT; Du D; Chen L; Dai R; Liu C; Yu G; Bhardwaj S; Parker SJ; Zhang Z; Clarke R; Herrington DM; Wang Y
    Bioinformatics; 2024 Mar; 40(3):. PubMed ID: 38407991
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Endometrial receptivity revisited: endometrial transcriptome adjusted for tissue cellular heterogeneity.
    Suhorutshenko M; Kukushkina V; Velthut-Meikas A; Altmäe S; Peters M; Mägi R; Krjutškov K; Koel M; Codoñer FM; Martinez-Blanch JF; Vilella F; Simón C; Salumets A; Laisk T
    Hum Reprod; 2018 Nov; 33(11):2074-2086. PubMed ID: 30295736
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Effective methods for bulk RNA-seq deconvolution using scnRNA-seq transcriptomes.
    Cobos FA; Panah MJN; Epps J; Long X; Man TK; Chiu HS; Chomsky E; Kiner E; Krueger MJ; di Bernardo D; Voloch L; Molenaar J; van Hooff SR; Westermann F; Jansky S; Redell ML; Mestdagh P; Sumazin P
    Genome Biol; 2023 Aug; 24(1):177. PubMed ID: 37528411
    [TBL] [Abstract][Full Text] [Related]  

  • 17. EPIC: A Tool to Estimate the Proportions of Different Cell Types from Bulk Gene Expression Data.
    Racle J; Gfeller D
    Methods Mol Biol; 2020; 2120():233-248. PubMed ID: 32124324
    [TBL] [Abstract][Full Text] [Related]  

  • 18. swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution.
    Chen L; Wu CT; Lin CH; Dai R; Liu C; Clarke R; Yu G; Van Eyk JE; Herrington DM; Wang Y
    Bioinformatics; 2022 Feb; 38(5):1403-1410. PubMed ID: 34904628
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Assessing transcriptomic heterogeneity of single-cell RNASeq data by bulk-level gene expression data.
    Tiong KL; Luzhbin D; Yeang CH
    BMC Bioinformatics; 2024 Jun; 25(1):209. PubMed ID: 38867193
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Systematic evaluation of transcriptomics-based deconvolution methods and references using thousands of clinical samples.
    Nadel BB; Oliva M; Shou BL; Mitchell K; Ma F; Montoya DJ; Mouton A; Kim-Hellmuth S; Stranger BE; Pellegrini M; Mangul S
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34346485
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.