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Journal Abstract Search

262 related items for PubMed ID: 22039215

  • 1. TIP: a probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles.
    Cheng C, Min R, Gerstein M.
    Bioinformatics; 2011 Dec 01; 27(23):3221-7. PubMed ID: 22039215
    [Abstract] [Full Text] [Related]

  • 2. iTAR: a web server for identifying target genes of transcription factors using ChIP-seq or ChIP-chip data.
    Yang CC, Andrews EH, Chen MH, Wang WY, Chen JJ, Gerstein M, Liu CC, Cheng C.
    BMC Genomics; 2016 Aug 12; 17(1):632. PubMed ID: 27519564
    [Abstract] [Full Text] [Related]

  • 3. ChIPXpress: using publicly available gene expression data to improve ChIP-seq and ChIP-chip target gene ranking.
    Wu G, Ji H.
    BMC Bioinformatics; 2013 Jun 10; 14():188. PubMed ID: 23758851
    [Abstract] [Full Text] [Related]

  • 4. Statistics of protein-DNA binding and the total number of binding sites for a transcription factor in the mammalian genome.
    Kuznetsov VA, Singh O, Jenjaroenpun P.
    BMC Genomics; 2010 Feb 10; 11 Suppl 1(Suppl 1):S12. PubMed ID: 20158869
    [Abstract] [Full Text] [Related]

  • 5. An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.
    Cheng CY, Chu CH, Hsu HW, Hsu FR, Tang CY, Wang WC, Kung HJ, Chang PC.
    BMC Genomics; 2014 Feb 10; 15 Suppl 1(Suppl 1):S1. PubMed ID: 24564277
    [Abstract] [Full Text] [Related]

  • 6. High resolution models of transcription factor-DNA affinities improve in vitro and in vivo binding predictions.
    Agius P, Arvey A, Chang W, Noble WS, Leslie C.
    PLoS Comput Biol; 2010 Sep 09; 6(9):. PubMed ID: 20838582
    [Abstract] [Full Text] [Related]

  • 7. Discovering transcription factor regulatory targets using gene expression and binding data.
    Maienschein-Cline M, Zhou J, White KP, Sciammas R, Dinner AR.
    Bioinformatics; 2012 Jan 15; 28(2):206-13. PubMed ID: 22084256
    [Abstract] [Full Text] [Related]

  • 8. Genome-wide identification of transcription factor-binding sites in plants using chromatin immunoprecipitation followed by microarray (ChIP-chip) or sequencing (ChIP-seq).
    Zhu JY, Sun Y, Wang ZY.
    Methods Mol Biol; 2012 Jan 15; 876():173-88. PubMed ID: 22576095
    [Abstract] [Full Text] [Related]

  • 9. A biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data.
    He X, Chen CC, Hong F, Fang F, Sinha S, Ng HH, Zhong S.
    PLoS One; 2009 Dec 01; 4(12):e8155. PubMed ID: 19956545
    [Abstract] [Full Text] [Related]

  • 10. The comprehensive transcriptional analysis in Caenorhabditis elegans by integrating ChIP-seq and gene expression data.
    He K, Shao J, Zhao Z, Liu D.
    Genet Res (Camb); 2014 Dec 01; 96():e005. PubMed ID: 25023089
    [Abstract] [Full Text] [Related]

  • 11. 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
    [Abstract] [Full Text] [Related]

  • 12. Positional distribution of human transcription factor binding sites.
    Koudritsky M, Domany E.
    Nucleic Acids Res; 2008 Dec 07; 36(21):6795-805. PubMed ID: 18953043
    [Abstract] [Full Text] [Related]

  • 13. MixChIP: a probabilistic method for cell type specific protein-DNA binding analysis.
    Rautio S, Lähdesmäki H.
    BMC Bioinformatics; 2015 Dec 24; 16():413. PubMed ID: 26703974
    [Abstract] [Full Text] [Related]

  • 14. Revealing transcription factor and histone modification co-localization and dynamics across cell lines by integrating ChIP-seq and RNA-seq data.
    Zhang L, Xue G, Liu J, Li Q, Wang Y.
    BMC Genomics; 2018 Dec 31; 19(Suppl 10):914. PubMed ID: 30598100
    [Abstract] [Full Text] [Related]

  • 15. Relationship between estrogen receptor alpha location and gene induction reveals the importance of downstream sites and cofactors.
    Parisi F, Sonderegger B, Wirapati P, Delorenzi M, Naef F.
    BMC Genomics; 2009 Aug 18; 10():381. PubMed ID: 19689805
    [Abstract] [Full Text] [Related]

  • 16. 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
    [Abstract] [Full Text] [Related]

  • 17. Most of the tight positional conservation of transcription factor binding sites near the transcription start site reflects their co-localization within regulatory modules.
    Acevedo-Luna N, Mariño-Ramírez L, Halbert A, Hansen U, Landsman D, Spouge JL.
    BMC Bioinformatics; 2016 Nov 21; 17(1):479. PubMed ID: 27871221
    [Abstract] [Full Text] [Related]

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