AlgPred: prediction of allergenic proteins and mapping of IgE epitopes.
AlgPred: prediction of allergenic proteins and mapping of IgE epitopes.
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DOI：
10.1093/nar/gkl343
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发表时间：
2006-07-01
影响因子：
14.9
通讯作者：
Raghava GP
中科院分区：
文献类型：
--
作者：
Saha S;Raghava GP
在这项研究中，系统地尝试整合各种方法，以预测过敏性蛋白质的高精度。用于测试和训练的数据集由从A. K. Bjorklund，D. Soeria-Atmadja，A.佐泽特大学Hammerling和M. G. Gustafsson（2005）Bioinformatics，21，39-50.首先，我们开发了基于支持向量机的方法，使用氨基酸和二肽的组成，并取得了85.02%和84.00%的准确率，分别。其次，使用MEME/MAST软件开发了基于基序的方法，其灵敏度为93.94，特异性为33.34%。第三，搜索已知IgE表位的数据库，这预测过敏原蛋白的灵敏度为17.47%，特异性为98.14%。第四，我们预测过敏原蛋白进行BLAST搜索过敏原代表肽。最后，已经开发了混合方法，其将两种或两种以上的方法组合联合收割机。所有这些算法的性能进行了评估的独立数据集的323过敏原和101 725非过敏原从瑞士Prot。开发了一个Web服务器AlgPred，用于预测过敏蛋白和绘制过敏蛋白上的IgE表位（）。AlgPred可在。
In this study a systematic attempt has been made to integrate various approaches in order to predict allergenic proteins with high accuracy. The dataset used for testing and training consists of 578 allergens and 700 non-allergens obtained from A. K. Bjorklund, D. Soeria-Atmadja, A. Zorzet, U. Hammerling and M. G. Gustafsson (2005) Bioinformatics, 21, 39–50. First, we developed methods based on support vector machine using amino acid and dipeptide composition and achieved an accuracy of 85.02 and 84.00%, respectively. Second, a motif-based method has been developed using MEME/MAST software that achieved sensitivity of 93.94 with 33.34% specificity. Third, a database of known IgE epitopes was searched and this predicted allergenic proteins with 17.47% sensitivity at specificity of 98.14%. Fourth, we predicted allergenic proteins by performing BLAST search against allergen representative peptides. Finally hybrid approaches have been developed, which combine two or more than two approaches. The performance of all these algorithms has been evaluated on an independent dataset of 323 allergens and on 101 725 non-allergens obtained from Swiss-Prot. A web server AlgPred has been developed for the predicting allergenic proteins and for mapping IgE epitopes on allergenic proteins (). AlgPred is available at .
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影响因子：
14.2
作者：
Broadfield, E;McKeever, TM;Britton, J
通讯作者：
Britton, J
影响因子：
14.9
作者：
Kumar, M;Bhasin, M;Natt, NK;Raghava, GPS
通讯作者：
Raghava, GPS
影响因子：
6.1
作者：
Ivanciuc, O;Mathura, V;Schein, CH
通讯作者：
Schein, CH
影响因子：
--
作者：
BRENDEL, V
通讯作者：
BRENDEL, V
影响因子：
--
作者：
Kleter, Gijs A;Peijnenburg, Ad A C M
通讯作者：
Peijnenburg, Ad A C M