A Clustering Approach for Motif Discovery in ChIP-Seq Dataset
| Autor: | Hua Wang, Yu Yang, Chun-xiao Sun, Wen-hu Wang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
motif discovery
planted motif search Computer science General Physics and Astronomy lcsh:Astrophysics DNA sequencing Article 03 medical and health sciences ChIP-Seq 0302 clinical medicine lcsh:QB460-466 Probabilistic analysis of algorithms Cluster analysis lcsh:Science 030304 developmental biology 0303 health sciences business.industry Pattern recognition Chip lcsh:QC1-999 DNA binding site 030220 oncology & carcinogenesis transcription factor binding sites Affinity propagation lcsh:Q Motif (music) Artificial intelligence business Chromatin immunoprecipitation lcsh:Physics |
| Zdroj: | Entropy Volume 21 Issue 8 Entropy, Vol 21, Iss 8, p 802 (2019) |
| ISSN: | 1099-4300 |
| DOI: | 10.3390/e21080802 |
| Popis: | Chromatin immunoprecipitation combined with next-generation sequencing (ChIP-Seq) technology has enabled the identification of transcription factor binding sites (TFBSs) on a genome-wide scale. To effectively and efficiently discover TFBSs in the thousand or more DNA sequences generated by a ChIP-Seq data set, we propose a new algorithm named AP-ChIP. First, we set two thresholds based on probabilistic analysis to construct and further filter the cluster subsets. Then, we use Affinity Propagation (AP) clustering on the candidate cluster subsets to find the potential motifs. Experimental results on simulated data show that the AP-ChIP algorithm is able to make an almost accurate prediction of TFBSs in a reasonable time. Also, the validity of the AP-ChIP algorithm is tested on a real ChIP-Seq data set. |
| Databáze: | OpenAIRE |
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