Tomtom home 2.7.5 download4/1/2023 ![]() ![]() This study has demonstrated the usefulness of CentriMo for TF binding specificity analysis.Ĭharacterising transcription factor binding sites (TFBS) is an important problem in bioinformatics, since predicting binding sites has many applications such as predicting gene regulation. We also show that the concentration of DEX treatment affects motif enrichment with 50nm being an optimum concentration for Gr binding by maintaining open chromatin via AP1 TF. IFN might reduce Cmyc and the Jun family of TFs binding via the repressive action of CTCF and E2f2. Enrichment of CTCF in Gm12878 with YY1 as the immuno-precipitated (ChIP-ed) factor and the presence of significant spacing (SpaMo analysis) of CTCF and YY1 in Gm12878 but not in K562 could show that CTCF, as a repressor, helps in maintaining the required YY1 level in a normal cell line. We observed differential motif enrichment of TFs with tumor promoter activity: YY1, CEBPA, Egr1, Cmyc family, Gata1 and JunD in K562 while Stat1, Irf1, and Runx1 in Gm12878. In this study, we investigate the use of CentriMo and other MEA tools to determine the difference in motif enrichment attributed presence of Chronic Myeloid leukemia (CML)), treatment with Interferon (IFN) and Dexamethasone (DEX) compared to control based on Fisher’s exact test using uniform peaks ChIP-seq data generated by the ENCODE consortium. One such tool, CentriMo, finds over-represented motifs at the center since peak calling software are biased to declaring binding regions centered at the TF binding site. Motif enrichment analysis (MEA) tools are used to identify motifs that are over-represented in ChIP-seq peak regions. ChIP-seq is an in vivo technique that considers how the chromatin landscape affects TF binding. Owing to its role in diseases, various techniques have been used to determine TF binding specificity in vitro and in vivo, including chromatin immuno-precipitation followed by massively parallel sequencing (ChIP-seq). TF binding specificity is how well a TF distinguishes functional sites from potential non-functional sites to form a useful regulatory network. ![]() They bind at various sites at different specificity depending on the prevailing cellular conditions, disease, development stage or environmental conditions of the cell. Transcription factors (TFs) are key regulators of gene expression whose failure has been implicated in many diseases, including cancer. ![]()
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