基于人工免疫系统的蛋白质-蛋白质相互作用网络聚类

Wang Chong, L. Xiujuan
{"title":"基于人工免疫系统的蛋白质-蛋白质相互作用网络聚类","authors":"Wang Chong, L. Xiujuan","doi":"10.3724/SP.J.1087.2013.03567","DOIUrl":null,"url":null,"abstract":"A Protein-Protein Interaction(PPI) network clustering model and an algorithm based on the mechanism of the Artificial Immune System(AIS) were proposed to improve the identification accuracy. In this algorithm,the set of cluster centers was regarded as antigens and the neighbor nodes were regarded as antibodies. The antibodies were regarded as the memory cells of clusters by calculating the affinity between the antibodies and antigens. Then excellent antibodies were selected as vaccines,and they were injected into clustering modules to get update. Finally the memory cells were updated after comparing the fitness of the modules before injection. The simulation results on PPI datasets show that,compared with FLOW algorithm,the f-measure of precision and recall value of the new algorithm have got improved.","PeriodicalId":61778,"journal":{"name":"计算机应用","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Protein-protein interaction network clustering based on artificial immune system\",\"authors\":\"Wang Chong, L. Xiujuan\",\"doi\":\"10.3724/SP.J.1087.2013.03567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Protein-Protein Interaction(PPI) network clustering model and an algorithm based on the mechanism of the Artificial Immune System(AIS) were proposed to improve the identification accuracy. In this algorithm,the set of cluster centers was regarded as antigens and the neighbor nodes were regarded as antibodies. The antibodies were regarded as the memory cells of clusters by calculating the affinity between the antibodies and antigens. Then excellent antibodies were selected as vaccines,and they were injected into clustering modules to get update. Finally the memory cells were updated after comparing the fitness of the modules before injection. The simulation results on PPI datasets show that,compared with FLOW algorithm,the f-measure of precision and recall value of the new algorithm have got improved.\",\"PeriodicalId\":61778,\"journal\":{\"name\":\"计算机应用\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"计算机应用\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.3724/SP.J.1087.2013.03567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"计算机应用","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3724/SP.J.1087.2013.03567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为了提高识别精度,提出了一种蛋白质-蛋白质相互作用(PPI)网络聚类模型和基于人工免疫系统(AIS)机制的算法。该算法将聚类中心集视为抗原,将相邻节点视为抗体。通过计算抗体与抗原的亲和力,将抗体作为集群的记忆细胞。然后选择优秀的抗体作为疫苗,注入聚类模块进行更新。最后在注射前比较各模块的适应度,更新记忆细胞。在PPI数据集上的仿真结果表明,与FLOW算法相比,新算法的精度f值和召回值都得到了提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Protein-protein interaction network clustering based on artificial immune system
A Protein-Protein Interaction(PPI) network clustering model and an algorithm based on the mechanism of the Artificial Immune System(AIS) were proposed to improve the identification accuracy. In this algorithm,the set of cluster centers was regarded as antigens and the neighbor nodes were regarded as antibodies. The antibodies were regarded as the memory cells of clusters by calculating the affinity between the antibodies and antigens. Then excellent antibodies were selected as vaccines,and they were injected into clustering modules to get update. Finally the memory cells were updated after comparing the fitness of the modules before injection. The simulation results on PPI datasets show that,compared with FLOW algorithm,the f-measure of precision and recall value of the new algorithm have got improved.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
23274
期刊介绍:
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信