BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

166 related articles for article (PubMed ID: 31125519)

  • 1. R Tutorial: Detection of Differentially Interacting Chromatin Regions From Multiple Hi-C Datasets.
    Stansfield JC; Tran D; Nguyen T; Dozmorov MG
    Curr Protoc Bioinformatics; 2019 Jun; 66(1):e76. PubMed ID: 31125519
    [TBL] [Abstract][Full Text] [Related]  

  • 2. HiCcompare: an R-package for joint normalization and comparison of HI-C datasets.
    Stansfield JC; Cresswell KG; Vladimirov VI; Dozmorov MG
    BMC Bioinformatics; 2018 Jul; 19(1):279. PubMed ID: 30064362
    [TBL] [Abstract][Full Text] [Related]  

  • 3. multiHiCcompare: joint normalization and comparative analysis of complex Hi-C experiments.
    Stansfield JC; Cresswell KG; Dozmorov MG
    Bioinformatics; 2019 Sep; 35(17):2916-2923. PubMed ID: 30668639
    [TBL] [Abstract][Full Text] [Related]  

  • 4. FreeHi-C spike-in simulations for benchmarking differential chromatin interaction detection.
    Zheng Y; Zhou P; Keleş S
    Methods; 2021 May; 189():3-11. PubMed ID: 32663510
    [TBL] [Abstract][Full Text] [Related]  

  • 5. diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data.
    Lun AT; Smyth GK
    BMC Bioinformatics; 2015 Aug; 16():258. PubMed ID: 26283514
    [TBL] [Abstract][Full Text] [Related]  

  • 6. HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking.
    Lazaris C; Kelly S; Ntziachristos P; Aifantis I; Tsirigos A
    BMC Genomics; 2017 Jan; 18(1):22. PubMed ID: 28056762
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Measuring significant changes in chromatin conformation with ACCOST.
    Cook KB; Hristov BH; Le Roch KG; Vert JP; Noble WS
    Nucleic Acids Res; 2020 Mar; 48(5):2303-2311. PubMed ID: 32034421
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Computational Analysis of Hi-C Data.
    Forcato M; Bicciato S
    Methods Mol Biol; 2021; 2157():103-125. PubMed ID: 32820401
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools.
    Freire-Pritchett P; Ray-Jones H; Della Rosa M; Eijsbouts CQ; Orchard WR; Wingett SW; Wallace C; Cairns J; Spivakov M; Malysheva V
    Nat Protoc; 2021 Sep; 16(9):4144-4176. PubMed ID: 34373652
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 3DIV: A 3D-genome Interaction Viewer and database.
    Yang D; Jang I; Choi J; Kim MS; Lee AJ; Kim H; Eom J; Kim D; Jung I; Lee B
    Nucleic Acids Res; 2018 Jan; 46(D1):D52-D57. PubMed ID: 29106613
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Utilizing networks for differential analysis of chromatin interactions.
    Liu L; Ruan J
    J Bioinform Comput Biol; 2017 Dec; 15(6):1740008. PubMed ID: 29113562
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines.
    Khalil AIS; Muzaki SRBM; Chattopadhyay A; Sanyal A
    BMC Bioinformatics; 2020 Nov; 21(1):506. PubMed ID: 33160308
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Tethered Chromosome Conformation Capture Sequencing in Triticeae: A Valuable Tool for Genome Assembly.
    Himmelbach A; Walde I; Mascher M; Stein N
    Bio Protoc; 2018 Aug; 8(15):e2955. PubMed ID: 34395764
    [TBL] [Abstract][Full Text] [Related]  

  • 14. GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data.
    Calandrelli R; Wu Q; Guan J; Zhong S
    Genomics Proteomics Bioinformatics; 2018 Oct; 16(5):365-372. PubMed ID: 30553884
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Mariner: explore the Hi-Cs.
    Davis ES; Parker SM; Kramer NE; Flores JP; Kiran M; Phanstiel DH
    Bioinformatics; 2024 Jun; 40(6):. PubMed ID: 38814811
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C.
    Hauth A; Galupa R; Servant N; Villacorta L; Hauschulz K; van Bemmel JG; Loda A; Heard E
    J Vis Exp; 2022 Oct; (188):. PubMed ID: 36314814
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Capture Hi-C Library Generation and Analysis to Detect Chromatin Interactions.
    Orlando G; Kinnersley B; Houlston RS
    Curr Protoc Hum Genet; 2018 Jul; 98(1):e63. PubMed ID: 29979818
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Evaluation of 3D Chromatin Interactions Using Hi-C.
    Hu G
    Methods Mol Biol; 2020; 2117():65-78. PubMed ID: 31960372
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments.
    Alinejad-Rokny H; Ghavami Modegh R; Rabiee HR; Ramezani Sarbandi E; Rezaie N; Tam KT; Forrest ARR
    PLoS Comput Biol; 2022 Jun; 18(6):e1010241. PubMed ID: 35749574
    [TBL] [Abstract][Full Text] [Related]  

  • 20. HiCeekR: A Novel Shiny App for Hi-C Data Analysis.
    Di Filippo L; Righelli D; Gagliardi M; Matarazzo MR; Angelini C
    Front Genet; 2019; 10():1079. PubMed ID: 31749839
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.