کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8876768 | 1623765 | 2018 | 32 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Recognition of the long range enhancer-promoter interactions by further adding DNA structure properties and transcription factor binding motifs in human cell lines
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کلمات کلیدی
GEOTFsGBMEPIAUROCHMSRPKMenhancer RNA - RNA تقویت کنندهeRNA - ارناEpigenetics - اپی ژنتیکHistone modifications - تغییرات هیستونRandom forest - جنگلهای تصادفی یا جنگلهای تصمیم تصادفیGradient Boosting Machine - دستگاه تقویت گرادیانTranscription factors - عوامل رونویسیarea under the receiver operating characteristic curve - محدوده تحت منحنی مشخصه عملکرد گیرندهGene Expression Omnibus - ژن بیان Omnibus
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم کشاورزی و بیولوژیک (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Recognition of the long range enhancer-promoter interactions by further adding DNA structure properties and transcription factor binding motifs in human cell lines Recognition of the long range enhancer-promoter interactions by further adding DNA structure properties and transcription factor binding motifs in human cell lines](/preview/png/8876768.png)
چکیده انگلیسی
The enhancer-promoter interactions (EPIs) with strong tissue-specificity play an important role in cis-regulatory mechanism of human cell lines. However, it still remains a challenging work to predict these interactions so far. Due to that these interactions are regulated by the cooperativeness of diverse functional genomic signatures, DNA spatial structure and DNA sequence elements. In this paper, by adding DNA structure properties and transcription factor binding motifs, we presented an improved computational method to predict EPIs in human cell lines. In comparison with the results of other group on the same datasets, our best accuracies by cross-validation test were about 15%-24% higher in the same cell lines, and the accuracies by independent test were about 11%-15% higher in new cell lines. Meanwhile, we found that transcription factor binding motifs and DNA structure properties have important information that would largely determine long range EPIs prediction. From the distribution comparisons, we also found their distinct differences between interacting and non-interacting sets in each cell line. Then, the correlation analysis and network models for relationships among top-ranked functional genomic signatures indicated that diverse genomic signatures would cooperatively establish a complex regulatory network to facilitate long range EPIs. The experimental results provided additional insights about the roles of DNA intrinsic properties and functional genomic signatures in EPIs prediction.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 445, 14 May 2018, Pages 136-150
Journal: Journal of Theoretical Biology - Volume 445, 14 May 2018, Pages 136-150
نویسندگان
Zhen-Xing Feng, Qian-Zhong Li, Jian-Jun Meng,