170 related articles for article (PubMed ID: 38225101)
1. Next-generation deconvolution of transcriptomic data to investigate the tumor microenvironment.
Merotto L; Zopoglou M; Zackl C; Finotello F
Int Rev Cell Mol Biol; 2024; 382():103-143. PubMed ID: 38225101
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Dissecting cellular states of infiltrating microenvironment cells in melanoma by integrating single-cell and bulk transcriptome analysis.
Shi A; Yan M; Pang B; Pang L; Wang Y; Lan Y; Zhang X; Xu J; Ping Y; Hu J
BMC Immunol; 2023 Dec; 24(1):52. PubMed ID: 38082384
[TBL] [Abstract][Full Text] [Related]
4. SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics.
Liu Z; Wu D; Zhai W; Ma L
Nat Commun; 2023 Aug; 14(1):4727. PubMed ID: 37550279
[TBL] [Abstract][Full Text] [Related]
5. Novel insights from spatial transcriptome analysis in solid tumors.
Du J; An ZJ; Huang ZF; Yang YC; Zhang MH; Fu XH; Shi WY; Hou J
Int J Biol Sci; 2023; 19(15):4778-4792. PubMed ID: 37781515
[TBL] [Abstract][Full Text] [Related]
6. Spatial transcriptomics in cancer research and potential clinical impact: a narrative review.
Cilento MA; Sweeney CJ; Butler LM
J Cancer Res Clin Oncol; 2024 Jun; 150(6):296. PubMed ID: 38850363
[TBL] [Abstract][Full Text] [Related]
7. In Silico Cell-Type Deconvolution Methods in Cancer Immunotherapy.
Sturm G; Finotello F; List M
Methods Mol Biol; 2020; 2120():213-222. PubMed ID: 32124322
[TBL] [Abstract][Full Text] [Related]
8. Applications of single-cell and bulk RNA sequencing in onco-immunology.
Kuksin M; Morel D; Aglave M; Danlos FX; Marabelle A; Zinovyev A; Gautheret D; Verlingue L
Eur J Cancer; 2021 May; 149():193-210. PubMed ID: 33866228
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. BEDwARS: a robust Bayesian approach to bulk gene expression deconvolution with noisy reference signatures.
Ghaffari S; Bouchonville KJ; Saleh E; Schmidt RE; Offer SM; Sinha S
Genome Biol; 2023 Aug; 24(1):178. PubMed ID: 37537644
[TBL] [Abstract][Full Text] [Related]
11. A reference profile-free deconvolution method to infer cancer cell-intrinsic subtypes and tumor-type-specific stromal profiles.
Wang L; Sebra RP; Sfakianos JP; Allette K; Wang W; Yoo S; Bhardwaj N; Schadt EE; Yao X; Galsky MD; Zhu J
Genome Med; 2020 Feb; 12(1):24. PubMed ID: 32111252
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures.
Zeng D; Ye Z; Shen R; Yu G; Wu J; Xiong Y; Zhou R; Qiu W; Huang N; Sun L; Li X; Bin J; Liao Y; Shi M; Liao W
Front Immunol; 2021; 12():687975. PubMed ID: 34276676
[TBL] [Abstract][Full Text] [Related]
15. A Comprehensive Overview of RNA Deconvolution Methods and Their Application.
Im Y; Kim Y
Mol Cells; 2023 Feb; 46(2):99-105. PubMed ID: 36859474
[TBL] [Abstract][Full Text] [Related]
16. Transcriptome profiling for precision cancer medicine using shallow nanopore cDNA sequencing.
Mock A; Braun M; Scholl C; Fröhling S; Erkut C
Sci Rep; 2023 Feb; 13(1):2378. PubMed ID: 36759549
[TBL] [Abstract][Full Text] [Related]
17. Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues.
Ahmed R; Zaman T; Chowdhury F; Mraiche F; Tariq M; Ahmad IS; Hasan A
Int J Mol Sci; 2022 Mar; 23(6):. PubMed ID: 35328458
[TBL] [Abstract][Full Text] [Related]
18. Computational solutions for spatial transcriptomics.
Kleino I; Frolovaitė P; Suomi T; Elo LL
Comput Struct Biotechnol J; 2022; 20():4870-4884. PubMed ID: 36147664
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology.
Valdes-Mora F; Handler K; Law AMK; Salomon R; Oakes SR; Ormandy CJ; Gallego-Ortega D
Front Immunol; 2018; 9():2582. PubMed ID: 30483257
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]