BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

168 related articles for article (PubMed ID: 34671028)

  • 21. cellsig plug-in enhances CIBERSORTx signature selection for multidataset transcriptomes with sparse multilevel modelling.
    Al Kamran Khan MA; Wu J; Sun Y; Barrow AD; Papenfuss AT; Mangiola S
    Bioinformatics; 2023 Dec; 39(12):. PubMed ID: 37952182
    [TBL] [Abstract][Full Text] [Related]  

  • 22. MuSiC2: cell-type deconvolution for multi-condition bulk RNA-seq data.
    Fan J; Lyu Y; Zhang Q; Wang X; Li M; Xiao R
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36208175
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Bayesian hierarchical error model for analysis of gene expression data.
    Cho H; Lee JK
    Bioinformatics; 2004 Sep; 20(13):2016-25. PubMed ID: 15044230
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A Bayesian mixture model for clustering droplet-based single-cell transcriptomic data from population studies.
    Sun Z; Chen L; Xin H; Jiang Y; Huang Q; Cillo AR; Tabib T; Kolls JK; Bruno TC; Lafyatis R; Vignali DAA; Chen K; Ding Y; Hu M; Chen W
    Nat Commun; 2019 Apr; 10(1):1649. PubMed ID: 30967541
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors.
    Hippen AA; Omran DK; Weber LM; Jung E; Drapkin R; Doherty JA; Hicks SC; Greene CS
    Genome Biol; 2023 Oct; 24(1):239. PubMed ID: 37864274
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Covariate-dependent negative binomial factor analysis of RNA sequencing data.
    Zamani Dadaneh S; Zhou M; Qian X
    Bioinformatics; 2018 Jul; 34(13):i61-i69. PubMed ID: 29949981
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Likelihood-based deconvolution of bulk gene expression data using single-cell references.
    Erdmann-Pham DD; Fischer J; Hong J; Song YS
    Genome Res; 2021 Oct; 31(10):1794-1806. PubMed ID: 34301624
    [TBL] [Abstract][Full Text] [Related]  

  • 29. De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution.
    Liao J; Qian J; Fang Y; Chen Z; Zhuang X; Zhang N; Shao X; Hu Y; Yang P; Cheng J; Hu Y; Yu L; Yang H; Zhang J; Lu X; Shao L; Wu D; Gao Y; Chen H; Fan X
    Nat Commun; 2022 Oct; 13(1):6498. PubMed ID: 36310179
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes.
    Zaitsev A; Chelushkin M; Dyikanov D; Cheremushkin I; Shpak B; Nomie K; Zyrin V; Nuzhdina E; Lozinsky Y; Zotova A; Degryse S; Kotlov N; Baisangurov A; Shatsky V; Afenteva D; Kuznetsov A; Paul SR; Davies DL; Reeves PM; Lanuti M; Goldberg MF; Tazearslan C; Chasse M; Wang I; Abdou M; Aslanian SM; Andrewes S; Hsieh JJ; Ramachandran A; Lyu Y; Galkin I; Svekolkin V; Cerchietti L; Poznansky MC; Ataullakhanov R; Fowler N; Bagaev A
    Cancer Cell; 2022 Aug; 40(8):879-894.e16. PubMed ID: 35944503
    [TBL] [Abstract][Full Text] [Related]  

  • 31. 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]  

  • 32. Omnibus and robust deconvolution scheme for bulk RNA sequencing data integrating multiple single-cell reference sets and prior biological knowledge.
    Chen C; Leung YY; Ionita M; Wang LS; Li M
    Bioinformatics; 2022 Sep; 38(19):4530-4536. PubMed ID: 35980155
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Bayesian transcriptome assembly.
    Maretty L; Sibbesen JA; Krogh A
    Genome Biol; 2014; 15(10):501. PubMed ID: 25367074
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Single cell transcriptomics in human osteoarthritis synovium and in silico deconvoluted bulk RNA sequencing.
    Huang ZY; Luo ZY; Cai YR; Chou CH; Yao ML; Pei FX; Kraus VB; Zhou ZK
    Osteoarthritis Cartilage; 2022 Mar; 30(3):475-480. PubMed ID: 34971754
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets.
    Maden SK; Kwon SH; Huuki-Myers LA; Collado-Torres L; Hicks SC; Maynard KR
    Genome Biol; 2023 Dec; 24(1):288. PubMed ID: 38098055
    [TBL] [Abstract][Full Text] [Related]  

  • 36. The Conjugation of Antibodies for the Simultaneous Detection of Surface Proteins and Transcriptome Analysis at a Single-Cell Level.
    Kleino I; Kekäläinen E; Lönnberg T
    Methods Mol Biol; 2020; 2184():31-45. PubMed ID: 32808216
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Computational deconvolution of transcriptomics data from mixed cell populations.
    Avila Cobos F; Vandesompele J; Mestdagh P; De Preter K
    Bioinformatics; 2018 Jun; 34(11):1969-1979. PubMed ID: 29351586
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Spatially informed cell-type deconvolution for spatial transcriptomics.
    Ma Y; Zhou X
    Nat Biotechnol; 2022 Sep; 40(9):1349-1359. PubMed ID: 35501392
    [TBL] [Abstract][Full Text] [Related]  

  • 39. BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data.
    Wang X; Sun Z; Zhang Y; Xu Z; Xin H; Huang H; Duerr RH; Chen K; Ding Y; Chen W
    Nucleic Acids Res; 2020 Jun; 48(11):5814-5824. PubMed ID: 32379315
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A Bayesian factorization method to recover single-cell RNA sequencing data.
    Wen ZH; Langsam JL; Zhang L; Shen W; Zhou X
    Cell Rep Methods; 2022 Jan; 2(1):100133. PubMed ID: 35474868
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.