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238 related items for PubMed ID: 31899481

  • 1. Application of topic models to a compendium of ChIP-Seq datasets uncovers recurrent transcriptional regulatory modules.
    Yang G, Ma A, Qin ZS, Chen L.
    Bioinformatics; 2020 Apr 15; 36(8):2352-2358. PubMed ID: 31899481
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  • 3. Improved linking of motifs to their TFs using domain information.
    Baumgarten N, Schmidt F, Schulz MH.
    Bioinformatics; 2020 Mar 01; 36(6):1655-1662. PubMed ID: 31742324
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  • 4. TFEA.ChIP: a tool kit for transcription factor binding site enrichment analysis capitalizing on ChIP-seq datasets.
    Puente-Santamaria L, Wasserman WW, Del Peso L.
    Bioinformatics; 2019 Dec 15; 35(24):5339-5340. PubMed ID: 31347689
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  • 6. UniBind: maps of high-confidence direct TF-DNA interactions across nine species.
    Puig RR, Boddie P, Khan A, Castro-Mondragon JA, Mathelier A.
    BMC Genomics; 2021 Jun 26; 22(1):482. PubMed ID: 34174819
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  • 10. MotifGenie: a Python application for searching transcription factor binding sequences using ChIP-Seq datasets.
    Oguztuzun C, Yasar P, Yavuz K, Muyan M, Can T.
    Bioinformatics; 2021 Nov 18; 37(22):4238-4239. PubMed ID: 33999190
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  • 11. SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles.
    Wong KC, Li Y, Peng C, Zhang Z.
    Bioinformatics; 2015 Jan 01; 31(1):17-24. PubMed ID: 25192742
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  • 12. Integrative analysis identifies co-dependent gene expression regulation of BRG1 and CHD7 at distal regulatory sites in embryonic stem cells.
    Yang P, Oldfield A, Kim T, Yang A, Yang JYH, Ho JWK.
    Bioinformatics; 2017 Jul 01; 33(13):1916-1920. PubMed ID: 28203701
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  • 13. Identification of transcription factor binding sites from ChIP-seq data at high resolution.
    Bardet AF, Steinmann J, Bafna S, Knoblich JA, Zeitlinger J, Stark A.
    Bioinformatics; 2013 Nov 01; 29(21):2705-13. PubMed ID: 23980024
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  • 16. Transcription factor-binding k-mer analysis clarifies the cell type dependency of binding specificities and cis-regulatory SNPs in humans.
    Tahara S, Tsuchiya T, Matsumoto H, Ozaki H.
    BMC Genomics; 2023 Oct 07; 24(1):597. PubMed ID: 37805453
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  • 17. MOCCS: Clarifying DNA-binding motif ambiguity using ChIP-Seq data.
    Ozaki H, Iwasaki W.
    Comput Biol Chem; 2016 Aug 07; 63():62-72. PubMed ID: 26971251
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  • 18. Crunch: integrated processing and modeling of ChIP-seq data in terms of regulatory motifs.
    Berger S, Pachkov M, Arnold P, Omidi S, Kelley N, Salatino S, van Nimwegen E.
    Genome Res; 2019 Jul 07; 29(7):1164-1177. PubMed ID: 31138617
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  • 19. ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data.
    Zhou KR, Liu S, Sun WJ, Zheng LL, Zhou H, Yang JH, Qu LH.
    Nucleic Acids Res; 2017 Jan 04; 45(D1):D43-D50. PubMed ID: 27924033
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  • 20. DiffChIPL: a differential peak analysis method for high-throughput sequencing data with biological replicates based on limma.
    Chen Y, Chen S, Lei EP.
    Bioinformatics; 2022 Sep 02; 38(17):4062-4069. PubMed ID: 35809062
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