基于集成模型的细菌必需基因识别算法研究及应用

项目名称： 基于集成模型的细菌必需基因识别算法研究及应用

项目编号： No.31470068

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 生物科学

项目作者： 郭锋彪

作者单位： 电子科技大学

项目金额： 30万元

中文摘要： 由于在抗菌药物设计、合成生物学及生命起源等各方面的重要性，细菌必需基因受到越来越多的重视。实验方法确定必需基因大多费时费力，科学家们逐渐地转向通过理论方法预测细菌的必需基因。考虑多种特征的集成模型被认为是最可靠的理论识别方法。本研究拟基于集成模型，发展特异性的大肠杆菌必需基因识别算法。对于每种特征（同源特征、序列特征、网络特征、保守域特征）都从表述形式上通过改善革新做到最优。然后采用主成分回归建立模型。由于该方法固有的优点，将同时实现特征筛选和预测分类的目的。主成分回归还可以同时解决样本数目不平衡的问题。大肠杆菌特异性模型将具有最高的识别准确率。把该模型经过修饰后应用到肺炎链球菌基因组，对必需性未知1637个基因进行判断，同时表明集成模型的可扩展性。本计划的顺利实施除了调研必需基因理论识别算法精度的极限，同时为发展基于集成模型的通用型识别算法做准备，从而促进细菌必需基因理论识别的发展。

中文关键词： 必需基因预测；特异性模型；集成方法；主成分回归；其他必需基因研究

英文摘要： Because of the importance in the fields of anti-bacterial drug design, synthetic biology and life origin researches,bacterial essential genes require more and more attentions. Using experimental methods to determine essential genes is so time-consuming and money-consuming that identifying essential genes by computational methods becomes necessary and important.The integrative model that combines multiple features is believed to be the most promising computational method. This project plans to develop E. coli specific essential gene identifying method based on integrative model. For each feature, it will be optimized in the descriptive forms. Then the principal component regression (PCR) will be used to combine the mutiple features to train the model.Because of its intrinsic characteristics,the PCR could filter the features and distinguish the samples at the same time. The PCR also could sucessively solve the problem of unbalanced sample sizes. The specific model for E. coli will attain the highest identifying accuracy. This model will be extended to the S. pneumoniae after some modification, and used to assign essentiality values for the retaining 1637 genes, and illustrating the expansibility of the method. The project aims to invesigating the maximum value of identifying essential genes in bacteria and would h

英文关键词： Identification of Essential genes；Specific model；Integrated method；Principal component regression (PCR)；Other related researches of essential genes