iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network.
iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network.
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iPTT(2 L)-CNN：通过卷积神经网络识别植物基因组启动子及其类型的两层预测器
DOI：
10.1155/2021/6636350
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发表时间：
2021
影响因子：
--
通讯作者：
Xu Z
中科院分区：
文献类型：
--
作者：
Sun A;Xiao X;Xu Z
A promoter is a short DNA sequence near to the start codon, responsible for initiating transcription of a specific gene in genome. The accurate recognition of promoters has great significance for a better understanding of the transcriptional regulation. Because of their importance in the process of biological transcriptional regulation, there is an urgent need to develop in silico tools to identify promoters and their types timely and accurately. A number of prediction methods had been developed in this regard; however, almost all of them were merely used for identifying promoters and their strength or sigma types. Owing to that TATA box region in TATA promoter that influences posttranscriptional processes, in the current study, we developed a two-layer predictor called iPTT(2L)-CNN by using the convolutional neural network (CNN) for identifying TATA and TATA-less promoters. The first layer can be used to identify a given DNA sequence as a promoter or nonpromoter. The second layer is used to identify whether the recognized promoter is TATA promoter or not. The 5-fold crossvalidation and independent testing results demonstrate that the constructed predictor is promising for identifying promoter and classifying TATA and TATA-less promoter. Furthermore, to make it easier for most experimental scientists get the results they need, a user-friendly web server has been established at http://www.jci-bioinfo.cn/iPPT(2L)-CNN.
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DOI：
10.1093/bioinformatics/bts565
发表时间：
2012-12-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Fu L;Niu B;Zhu Z;Wu S;Li W
通讯作者：
Li W
iPromoter-2L2.0：结合平滑切割窗口算法和基于序列的特征来识别启动子及其类型
影响因子：
8.8
作者：
Liu, Bin;Li, Kai
通讯作者：
Li, Kai
影响因子：
5.8
作者：
Liang, Zhi-Yong;Lai, Hong-Yan;Lin, Hao
通讯作者：
Lin, Hao
影响因子：
5.8
作者：
Amin, Ruhul;Rahman, Chowdhury Rafeed;Shatabda, Swakkhar
通讯作者：
Shatabda, Swakkhar
iPro54-PseKNC：基于序列的预测因子，用于识别具有伪 k 元核苷酸组成的原核生物中的 sigma-54 启动子
影响因子：
14.9
作者：
Lin H;Deng EZ;Ding H;Chen W;Chou KC
通讯作者：
Chou KC