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.
163 related articles for article (PubMed ID: 34025950)
1. HCMB: A stable and efficient algorithm for processing the normalization of highly sparse Hi-C contact data. Wu H; Wang X; Chu M; Li D; Cheng L; Zhou K Comput Struct Biotechnol J; 2021; 19():2637-2645. PubMed ID: 34025950 [TBL] [Abstract][Full Text] [Related]
2. 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]
3. normGAM: an R package to remove systematic biases in genome architecture mapping data. Liu T; Wang Z BMC Genomics; 2019 Dec; 20(Suppl 12):1006. PubMed ID: 31888469 [TBL] [Abstract][Full Text] [Related]
4. HiConfidence: a novel approach uncovering the biological signal in Hi-C data affected by technical biases. Kobets VA; Ulianov SV; Galitsyna AA; Doronin SA; Mikhaleva EA; Gelfand MS; Shevelyov YY; Razin SV; Khrameeva EE Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36759336 [TBL] [Abstract][Full Text] [Related]
5. Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data. Li W; Gong K; Li Q; Alber F; Zhou XJ Bioinformatics; 2015 Mar; 31(6):960-2. PubMed ID: 25391400 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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]
8. Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model. Fang T; Liu Y; Woicik A; Lu M; Jha A; Wang X; Li G; Hristov B; Liu Z; Xu H; Noble WS; Wang S Bioinformatics; 2024 Jun; 40(Supplement_1):i471-i480. PubMed ID: 38940142 [TBL] [Abstract][Full Text] [Related]
9. covNorm: An R package for coverage based normalization of Hi-C and capture Hi-C data. Kim K; Jung I Comput Struct Biotechnol J; 2021; 19():3149-3159. PubMed ID: 34141136 [TBL] [Abstract][Full Text] [Related]
10. EnHiC: learning fine-resolution Hi-C contact maps using a generative adversarial framework. Hu Y; Ma W Bioinformatics; 2021 Jul; 37(Suppl_1):i272-i279. PubMed ID: 34252966 [TBL] [Abstract][Full Text] [Related]
12. Identifying TAD-like domains on single-cell Hi-C data by graph embedding and changepoint detection. Liu E; Lyu H; Liu Y; Fu L; Cheng X; Yin X Bioinformatics; 2024 Mar; 40(3):. PubMed ID: 38449288 [TBL] [Abstract][Full Text] [Related]
15. FAN-C: a feature-rich framework for the analysis and visualisation of chromosome conformation capture data. Kruse K; Hug CB; Vaquerizas JM Genome Biol; 2020 Dec; 21(1):303. PubMed ID: 33334380 [TBL] [Abstract][Full Text] [Related]
16. ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data. Oluwadare O; Cheng J BMC Bioinformatics; 2017 Nov; 18(1):480. PubMed ID: 29137603 [TBL] [Abstract][Full Text] [Related]
17. GRiNCH: simultaneous smoothing and detection of topological units of genome organization from sparse chromatin contact count matrices with matrix factorization. Lee DI; Roy S Genome Biol; 2021 May; 22(1):164. PubMed ID: 34034791 [TBL] [Abstract][Full Text] [Related]
18. Pentad: a tool for distance-dependent analysis of Hi-C interactions within and between chromatin compartments. Magnitov MD; Garaev AK; Tyakht AV; Ulianov SV; Razin SV BMC Bioinformatics; 2022 Apr; 23(1):116. PubMed ID: 35366792 [TBL] [Abstract][Full Text] [Related]