基于群优化拟合及临床数据的癌症lncRNA预测技术研究  

Prediction Technology Study of Cancer lncRNA Based on Swarm Optimization Fitting and Clinical Data

作　　者：王波 李玲玲[3] 刘佰泉 陶佰睿 李敬有[4] WANG Bo;LI Lingling;LIU Baiquan;TAO Bairui;LI Jingyou(College of Computer and Control,Qiqihar University,Qiqihar 161006,China;College of Computer Science and Technology,Harbin Engineering University,Harbin 150001,China;Network Information Center,Qiqihar University,Qiqihar 161006,China;School of Communications and Electrical Engineering,Qiqihar University,Qiqihar 161006,China)

机构地区：[1]齐齐哈尔大学计算机与控制工程学院,黑龙江齐齐哈尔161006 [2]哈尔滨工程大学计算机科学与技术学院,黑龙江哈尔滨150001 [3]齐齐哈尔大学网络信息中心,黑龙江齐齐哈尔161006 [4]齐齐哈尔大学通信与电子工程学院,黑龙江齐齐哈尔161006

出　　处：《现代信息科技》2020年第16期8-12,共5页Modern Information Technology

基　　金：黑龙江省教育厅基本科研业务专项(135109249)。

摘　　要：提出一种群优化拟合方法,通过测试函数和优化模型,分析验证了其具有较好的优化能力。采用群优化拟合方法计算了关键特征集合,并结合临床数据提出了一种基于群优化拟合及临床数据的癌症lncRNA预测方法。该方法在关键特征集合的基础上采用判别分析完成预测,预测过程中采用马氏统计距离的最小原则。实验结果表明,该方法获得了较好的收敛性能,在精确度、召回率和F1-Score三个指标上都达到了较好的预测结果。In this paper,a method of swarm optimization fitting was proposed,which was proved to have good optimization ability by test function and optimization model.The pivotal feature set was calculated by the method of swarm optimization fitting,and a prediction method of cancer lncRNA based on swarm optimization fitting and clinical data was proposed in combination with clinical data.The method used discriminant analysis to complete the prediction based on pivotal feature set,and the Mahalanobis statistical distance principle was adopted in the prediction process.Experimental results show that this method achieved good convergence performance and good prediction results in accuracy,recall rate and F1-Score.

关 键 词：群优化拟合 临床数据 lncRNA预测技术 癌症 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]