Predicting nucleosome positioning based on geometrically transformed Tsallis entropy.
As the fundamental unit of eukaryotic chromatin structure, nucleosome plays critical roles in gene expression and regulation by controlling physical access to transcription factors. In this paper, based on the geometrically transformed Tsallis entropy and two index-vectors, a valid nucleosome positioning information model is developed to describe the distribution of A/T-riched and G/C-riched dimeric and trimeric motifs along the DNA duplex. When applied to train the support vector machine, the model achieves high AUCs across five organisms, which have significantly outperformed the previous studies. Besides, we adopt the concept of relative distance to describe the probability of arbitrary DNA sequence covered by nucleosome. Thus, the average nucleosome occupancy profile over the S.cerevisiae genome is calculated. With our peak detection model, the isolated nucleosomes along genome sequence are located. When compared with some published results, it shows that our model is effective for nucleosome positioning. The index-vector component [Formula in text] is identified to be an important influencing factor of nucleosome organizations.
School of Mathematics and Statistics, Shandong University at Weihai, Weihai, China.
Jing
J
Wu
School of Mathematics and Statistics, Shandong University at Weihai, Weihai, China.
Yusen
Y
Zhang
School of Mathematics and Statistics, Shandong University at Weihai, Weihai, China.
Zengchao
Z
Mu
D019295:Computational Biology / Q000379:methods*; D019277:Entropy; D023281:Genomics; D006801:Humans; D008954:Models, Biological; D009707:Nucleosomes / Q000235:genetics / Q000378:metabolism*; D059372:Nucleotide Motifs; D060388:Support Vector Machine
D009707:Nucleosomes