330 related articles for article (PubMed ID: 32029002)
1. Integrative prediction of gene expression with chromatin accessibility and conformation data.
Schmidt F; Kern F; Schulz MH
Epigenetics Chromatin; 2020 Feb; 13(1):4. PubMed ID: 32029002
[TBL] [Abstract][Full Text] [Related]
2. Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility.
Liu S; Zibetti C; Wan J; Wang G; Blackshaw S; Qian J
BMC Bioinformatics; 2017 Jul; 18(1):355. PubMed ID: 28750606
[TBL] [Abstract][Full Text] [Related]
3. Enhancer prediction in the human genome by probabilistic modelling of the chromatin feature patterns.
Osmala M; Lähdesmäki H
BMC Bioinformatics; 2020 Jul; 21(1):317. PubMed ID: 32689977
[TBL] [Abstract][Full Text] [Related]
4. HiCoP, a simple and robust method for detecting interactions of regulatory regions.
Zhang Y; Li Z; Bian S; Zhao H; Feng D; Chen Y; Hou Y; Liu Q; Hao B
Epigenetics Chromatin; 2020 Jul; 13(1):27. PubMed ID: 32611439
[TBL] [Abstract][Full Text] [Related]
5. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.
Schmidt F; Gasparoni N; Gasparoni G; Gianmoena K; Cadenas C; Polansky JK; Ebert P; Nordström K; Barann M; Sinha A; Fröhler S; Xiong J; Dehghani Amirabad A; Behjati Ardakani F; Hutter B; Zipprich G; Felder B; Eils J; Brors B; Chen W; Hengstler JG; Hamann A; Lengauer T; Rosenstiel P; Walter J; Schulz MH
Nucleic Acids Res; 2017 Jan; 45(1):54-66. PubMed ID: 27899623
[TBL] [Abstract][Full Text] [Related]
6. BinDNase: a discriminatory approach for transcription factor binding prediction using DNase I hypersensitivity data.
Kähärä J; Lähdesmäki H
Bioinformatics; 2015 Sep; 31(17):2852-9. PubMed ID: 25957350
[TBL] [Abstract][Full Text] [Related]
7. Probing transcription factor combinatorics in different promoter classes and in enhancers.
Vandel J; Cassan O; Lèbre S; Lecellier CH; Bréhélin L
BMC Genomics; 2019 Feb; 20(1):103. PubMed ID: 30709337
[TBL] [Abstract][Full Text] [Related]
8. Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.
Tsai ZT; Shiu SH; Tsai HK
PLoS Comput Biol; 2015 Aug; 11(8):e1004418. PubMed ID: 26291518
[TBL] [Abstract][Full Text] [Related]
9. Identification of significant chromatin contacts from HiChIP data by FitHiChIP.
Bhattacharyya S; Chandra V; Vijayanand P; Ay F
Nat Commun; 2019 Sep; 10(1):4221. PubMed ID: 31530818
[TBL] [Abstract][Full Text] [Related]
10. Hierarchical cooperation of transcription factors from integration analysis of DNA sequences, ChIP-Seq and ChIA-PET data.
Wang R; Wang Y; Zhang X; Zhang Y; Du X; Fang Y; Li G
BMC Genomics; 2019 May; 20(Suppl 3):296. PubMed ID: 32039697
[TBL] [Abstract][Full Text] [Related]
11. DeepCAGE: Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility.
Liu Q; Hua K; Zhang X; Wong WH; Jiang R
Genomics Proteomics Bioinformatics; 2022 Jun; 20(3):496-507. PubMed ID: 35293310
[TBL] [Abstract][Full Text] [Related]
12. Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network.
Zeng W; Wang Y; Jiang R
Bioinformatics; 2020 Jan; 36(2):496-503. PubMed ID: 31318408
[TBL] [Abstract][Full Text] [Related]
13. 7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs.
Ibn-Salem J; Andrade-Navarro MA
BMC Genomics; 2019 Oct; 20(1):777. PubMed ID: 31653198
[TBL] [Abstract][Full Text] [Related]
14. Early adaptive chromatin remodeling events precede pathologic phenotypes and are reinforced in the failing heart.
Chapski DJ; Cabaj M; Morselli M; Mason RJ; Soehalim E; Ren S; Pellegrini M; Wang Y; Vondriska TM; Rosa-Garrido M
J Mol Cell Cardiol; 2021 Nov; 160():73-86. PubMed ID: 34273410
[TBL] [Abstract][Full Text] [Related]
15. In the loop: promoter-enhancer interactions and bioinformatics.
Mora A; Sandve GK; Gabrielsen OS; Eskeland R
Brief Bioinform; 2016 Nov; 17(6):980-995. PubMed ID: 26586731
[TBL] [Abstract][Full Text] [Related]
16. Mechanisms of Interplay between Transcription Factors and the 3D Genome.
Kim S; Shendure J
Mol Cell; 2019 Oct; 76(2):306-319. PubMed ID: 31521504
[TBL] [Abstract][Full Text] [Related]
17. ATAC-seq reveals regional differences in enhancer accessibility during the establishment of spatial coordinates in the
Bozek M; Cortini R; Storti AE; Unnerstall U; Gaul U; Gompel N
Genome Res; 2019 May; 29(5):771-783. PubMed ID: 30962180
[TBL] [Abstract][Full Text] [Related]
18. Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development.
Phanstiel DH; Van Bortle K; Spacek D; Hess GT; Shamim MS; Machol I; Love MI; Aiden EL; Bassik MC; Snyder MP
Mol Cell; 2017 Sep; 67(6):1037-1048.e6. PubMed ID: 28890333
[TBL] [Abstract][Full Text] [Related]
19. Chromatin accessibility dynamics reveal novel functional enhancers in
Daugherty AC; Yeo RW; Buenrostro JD; Greenleaf WJ; Kundaje A; Brunet A
Genome Res; 2017 Dec; 27(12):2096-2107. PubMed ID: 29141961
[TBL] [Abstract][Full Text] [Related]
20. Integrative characterization of G-Quadruplexes in the three-dimensional chromatin structure.
Hou Y; Li F; Zhang R; Li S; Liu H; Qin ZS; Sun X
Epigenetics; 2019 Sep; 14(9):894-911. PubMed ID: 31177910
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
