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1
Mariner: explore the Hi-Cs.
Bioinformatics. 2024 Jun 3;40(6). doi: 10.1093/bioinformatics/btae352.
2
CWL-Based Analysis Pipeline for Hi-C Data: From FASTQ Files to Matrices.
Methods Mol Biol. 2025;2856:79-117. doi: 10.1007/978-1-0716-4136-1_6.
3
HiCcompare: an R-package for joint normalization and comparison of HI-C datasets.
BMC Bioinformatics. 2018 Jul 31;19(1):279. doi: 10.1186/s12859-018-2288-x.
5
ReactomeGSA: new features to simplify public data reuse.
Bioinformatics. 2024 Jun 3;40(6). doi: 10.1093/bioinformatics/btae338.
6
RepViz: a replicate-driven R tool for visualizing genomic regions.
BMC Res Notes. 2019 Jul 19;12(1):441. doi: 10.1186/s13104-019-4473-z.
7
Sushi.R: flexible, quantitative and integrative genomic visualizations for publication-quality multi-panel figures.
Bioinformatics. 2014 Oct;30(19):2808-10. doi: 10.1093/bioinformatics/btu379. Epub 2014 Jun 5.
8
Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model.
Bioinformatics. 2024 Jun 28;40(Suppl 1):i471-i480. doi: 10.1093/bioinformatics/btae211.
9
GDCRNATools: an R/Bioconductor package for integrative analysis of lncRNA, miRNA and mRNA data in GDC.
Bioinformatics. 2018 Jul 15;34(14):2515-2517. doi: 10.1093/bioinformatics/bty124.
10
UMI4Cats: an R package to analyze chromatin contact profiles obtained by UMI-4C.
Bioinformatics. 2021 Nov 18;37(22):4240-4242. doi: 10.1093/bioinformatics/btab392.

引用本文的文献

1
Genome reorganization and its functional impact during breast cancer progression.
bioRxiv. 2025 May 17:2025.05.14.654144. doi: 10.1101/2025.05.14.654144.
2
A Bioconductor/R Workflow for the Detection and Visualization of Differential Chromatin Loops.
F1000Res. 2024 Nov 11;13:1346. doi: 10.12688/f1000research.153949.1. eCollection 2024.
6
Guiding the design of well-powered Hi-C experiments to detect differential loops.
bioRxiv. 2023 Mar 16:2023.03.15.532762. doi: 10.1101/2023.03.15.532762.

本文引用的文献

1
Cooltools: Enabling high-resolution Hi-C analysis in Python.
PLoS Comput Biol. 2024 May 6;20(5):e1012067. doi: 10.1371/journal.pcbi.1012067. eCollection 2024 May.
2
HiCmapTools: a tool to access HiC contact maps.
BMC Bioinformatics. 2022 Feb 10;23(1):64. doi: 10.1186/s12859-022-04589-y.
3
Plotgardener: cultivating precise multi-panel figures in R.
Bioinformatics. 2022 Mar 28;38(7):2042-2045. doi: 10.1093/bioinformatics/btac057.
4
HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP.
Nat Commun. 2021 Jun 7;12(1):3366. doi: 10.1038/s41467-021-23749-x.
5
Coolpup.py: versatile pile-up analysis of Hi-C data.
Bioinformatics. 2020 May 1;36(10):2980-2985. doi: 10.1093/bioinformatics/btaa073.
6
Juicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments.
Cell Syst. 2016 Jul;3(1):95-8. doi: 10.1016/j.cels.2016.07.002.
7
Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experiments.
F1000Res. 2016 May 20;5:950. doi: 10.12688/f1000research.8759.2. eCollection 2016.
8
HiC-Pro: an optimized and flexible pipeline for Hi-C data processing.
Genome Biol. 2015 Dec 1;16:259. doi: 10.1186/s13059-015-0831-x.
9
Bioconductor: open software development for computational biology and bioinformatics.
Genome Biol. 2004;5(10):R80. doi: 10.1186/gb-2004-5-10-r80. Epub 2004 Sep 15.

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