BPROMPT: a consensus server for membrane protein prediction
BPROMPT: a consensus server for membrane protein prediction
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DOI：
10.1093/nar/gkg554
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发表时间：
2003-07-01
影响因子：
14.9
通讯作者：
Flower, DR
中科院分区：
文献类型：
--
作者：
Taylor, PD;Attwood, TK;Flower, DR
蛋白质结构预测是生物信息学研究的基石。膜蛋白由于其固有的不同组成需要它们自己的预测方法。存在多种用于膜蛋白的拓扑预测的工具，其中许多可在因特网上获得。本文描述的服务器BPROMPT（Bayesian Prediction Of Membrane Protein Topology）使用贝叶斯置信网络（Bayesian Belief Network）来联合收割机结合其他预测方法的结果，提供更准确的一致性预测。原核生物和真核生物的拓扑结构预测的准确率分别为70%和53%。BPROMPT可以在www.example.com上访问。
Protein structure prediction is a cornerstone of bioinformatics research. Membrane proteins require their own prediction methods due to their intrinsically different composition. A variety of tools exist for topology prediction of membrane proteins, many of them available on the Internet. The server described in this paper, BPROMPT (Bayesian PRediction Of Membrane Protein Topology), uses a Bayesian Belief Network to combine the results of other prediction methods, providing a more accurate consensus prediction. Topology predictions with accuracies of 70% for prokaryotes and 53% for eukaryotes were achieved. BPROMPT can be accessed at http://www.jenner.ac.uk/BPROMPT.