首页> 美国卫生研究院文献>Bioinformation >RetroPred: A tool for prediction classification and extraction of non-LTR retrotransposons (LINEs SINEs) from the genome by integrating PALS PILER MEME and ANN
【2h】

RetroPred: A tool for prediction classification and extraction of non-LTR retrotransposons (LINEs SINEs) from the genome by integrating PALS PILER MEME and ANN

机译:RetroPred:通过整合PALSPILERMEME和ANN从基因组预测分类和提取非LTR逆转座子(LINEs和SINEs)的工具

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。
获取外文期刊封面目录资料

摘要

The problem of predicting non-long terminal repeats (LTR) like long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs) from the DNA sequence is still an open problem in bioinformatics. To elevate the quality of annotations of LINES and SINEs an automated tool “RetroPred” was developed. The pipeline allowed rapid and thorough annotation of non-LTR retrotransposons. The non-LTR retrotransposable elements were initially predicted by Pairwise Aligner for Long Sequences (PALS) and Parsimonious Inference of a Library of Elementary Repeats (PILER). Predicted non-LTR elements were automatically classified into LINEs and SINEs using ANN based on the position specific probability matrix (PSPM) generated by Multiple EM for Motif Elicitation (MEME). The ANN model revealed a superior model (accuracy = 78.79 ± 6.86 %, Qpred = 74.734 ± 17.08 %, sensitivity = 84.48 ± 6.73 %, specificity = 77.13 ± 13.39 %) using four-fold cross validation. As proof of principle, we have thoroughly annotated the location of LINEs and SINEs in rice and Arabidopsis genome using the tool and is proved to be very useful with good accuracy. Our tool is accessible at .
机译:从DNA序列预测非长末端重复序列(LTR)的问题,如长散布的核元件(LINEs)和短散布的核元件(SINEs),仍然是生物信息学中的未解决问题。为了提高LINES和SINE的注释的质量,开发了自动化工具“ RetroPred”。管道可以快速彻底地注释非LTR逆转座子。非LTR逆转座因子最初由长序列成对比对(PALS)和基本重复文库的简约推断(PILER)预测。基于由多个EM进行主题动机(MEME)生成的位置特定概率矩阵(PSPM),使用ANN将预测的非LTR元素自动分类为LINE和SINE。 ANN模型使用四重交叉验证显示了一个优越的模型(准确性= 78.79±6.86%,Qpred = 74.734±17.08%,灵敏度= 84.48±6.73%,特异性= 77.13±13.39%)。作为原理上的证明,我们已使用该工具彻底注释了LINE和SINE在水稻和拟南芥基因组中的位置,并被证明非常有用且准确性很高。可通过访问我们的工具。

著录项

相似文献

  • 外文文献
  • 中文文献
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号