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PiRaNhA:一种用于预测蛋白质序列中 RNA 结合残基的计算服务器。

PiRaNhA: a server for the computational prediction of RNA-binding residues in protein sequences.

机构信息

Laboratory of Protein Informatics, Research Center for Structural and Functional Proteomics, Institute for Protein Research, Osaka University, Osaka, Japan.

出版信息

Nucleic Acids Res. 2010 Jul;38(Web Server issue):W412-6. doi: 10.1093/nar/gkq474. Epub 2010 May 27.

Abstract

The PiRaNhA web server is a publicly available online resource that automatically predicts the location of RNA-binding residues (RBRs) in protein sequences. The goal of functional annotation of sequences in the field of RNA binding is to provide predictions of high accuracy that require only small numbers of targeted mutations for verification. The PiRaNhA server uses a support vector machine (SVM), with position-specific scoring matrices, residue interface propensity, predicted residue accessibility and residue hydrophobicity as features. The server allows the submission of up to 10 protein sequences, and the predictions for each sequence are provided on a web page and via email. The prediction results are provided in sequence format with predicted RBRs highlighted, in text format with the SVM threshold score indicated and as a graph which enables users to quickly identify those residues above any specific SVM threshold. The graph effectively enables the increase or decrease of the false positive rate. When tested on a non-redundant data set of 42 protein sequences not used in training, the PiRaNhA server achieved an accuracy of 85%, specificity of 90% and a Matthews correlation coefficient of 0.41 and outperformed other publicly available servers. The PiRaNhA prediction server is freely available at http://www.bioinformatics.sussex.ac.uk/PIRANHA.

摘要

PiRaNhA 网络服务器是一个公共可用的在线资源,可自动预测蛋白质序列中 RNA 结合残基 (RBR) 的位置。在 RNA 结合领域对序列进行功能注释的目标是提供仅需少量靶向突变即可验证的高精度预测。PiRaNhA 服务器使用支持向量机 (SVM),具有位置特异性评分矩阵、残基界面倾向、预测残基可及性和残基疏水性作为特征。该服务器允许提交多达 10 个蛋白质序列,并且为每个序列提供网页和电子邮件上的预测结果。预测结果以序列格式提供,突出显示预测的 RBR,以文本格式提供 SVM 阈值分数,并以图形形式提供,使用户能够快速识别任何特定 SVM 阈值以上的残基。该图形有效地增加或减少了假阳性率。在一个非冗余的 42 个蛋白质序列数据集上进行测试,这些序列未用于训练,PiRaNhA 服务器的准确率为 85%,特异性为 90%,马修斯相关系数为 0.41,优于其他公开可用的服务器。PiRaNhA 预测服务器可免费在 http://www.bioinformatics.sussex.ac.uk/PIRANHA 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64eb/2896099/deb016914b12/gkq474f1.jpg

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