A Clustering Approach for Motif Discovery in ChIP-Seq Dataset
نویسندگان
چکیده
منابع مشابه
DREME: motif discovery in transcription factor ChIP-seq data
MOTIVATION Transcription factor (TF) ChIP-seq datasets have particular characteristics that provide unique challenges and opportunities for motif discovery. Most existing motif discovery algorithms do not scale well to such large datasets, or fail to report many motifs associated with cofactors of the ChIP-ed TF. RESULTS We present DREME, a motif discovery algorithm specifically designed to f...
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De novo motif discovery is a difficult computational task. Historically, dedicated algorithms always reported a high percentage of false positives. Their performance did not improve considerably even after they adapted to handle large amounts of chromatin immunoprecipitation sequencing (ChIP-Seq) data. Several studies have advocated aggregating complementary algorithms, combining their predicti...
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Identification of DNA motifs from ChIP-seq/ChIP-chip [chromatin immunoprecipitation (ChIP)] data is a powerful method for understanding the transcriptional regulatory network. However, most established methods are designed for small sample sizes and are inefficient for ChIP data. Here we propose a new k-mer occurrence model to reflect the fact that functional DNA k-mers often cluster around ChI...
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Summary: High-throughput sequencing technologies such as ChIPseq have deepened our understanding in many biological processes. De novo motif search is one of the key downstream computational analysis following the ChIP-seq experiments and several algorithms have been proposed for this purpose. However, most webbased systems do not perform independent filtering or enrichment analyses to ensure t...
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MOTIVATION Building an accurate binding model for a transcription factor (TF) is essential to differentiate its true binding targets from those spurious ones. This is an important step toward understanding gene regulation. RESULTS This paper describes a boosting approach to modeling TF-DNA binding. Different from the widely used weight matrix model, which predicts TF-DNA binding based on a li...
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ژورنال
عنوان ژورنال: Entropy
سال: 2019
ISSN: 1099-4300
DOI: 10.3390/e21080802