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禽流感信息系统的构建
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摘要
自2003年以来,全球爆发H5N1亚型高致病性禽流感,导致了严重的经济损失并引起广泛的社会关注。A型禽流感病毒可以跨宿主直接感染人和其它高等哺乳动物,虽暂时不具备人群内传播的特性,但已初步适应人等哺乳动物,具有大流行的趋势。禽源和人源禽流感病毒的分子序列差异和禽流感病毒的跨宿主性是一个值得探讨的问题。为了方便对禽流感病毒进行生物信息学研究,建立禽流感信息系统十分必要。
     本文将国际权威的ISD和NCBI的IVR禽流感病毒数据库的数据本地化,利用Python、CGI等相关技术,建立禽流感病毒数据库FLU-KEY。在该数据库的基础上,利用HTML、Python以及CGI技术建立Web搜索系统,并采用了包含所有6个禽流感病毒内部蛋白序列的搜索方式,提高搜索质量,提供对符合搜索条件的数据提供fasta格式下载,极大地方便了对禽流感病毒的生物信息学研究。
     为了对禽流感数据进行初步统计,得到感性认识以及地理统计规律,本文采用Google Maps API技术建立图形显示系统。该系统能够动态地显示用户输入的时间段内整个世界的禽流感毒株分布。
     在禽流感跨宿主研究方面,本文还开发了一个禽流感病毒跨宿主性分类器。该分类器将用户新分离到的流感病毒基因组序列进行转换并采用小波包分解的方法提取能量特征,对每株病毒的能量特征值,采用KNN法对已有的跨宿主传播表型的相关模式进行欧几里德距离的计算,从而得出该毒株是否具有跨宿主性。利用Python的Biopython模块和PyWavelets模块,将该分类器整合到禽流感信息系统中,提供Web服务。
     使用该禽流感信息系统,一方面可以搜索、下载感兴趣的禽流感病毒数据进行生物信息学研究,另一方面可以对新分离到的禽流感毒株进行分析和预测,从而对该毒株是否具有跨宿主传染性进行预警。
H5N1 viruses were continuously reported from 2003 and caused serious economic loss. Much social attention has been focused on that. Avian Influenza A viruses could directly infect human and mammal. Although avian influenza viruses could not spread among crowd, they had partly been adapted to human and mammal hosts and that could result in pandemics. The differences between the sequences of avian influenza viruses are important and valuable to be studied, especially the molecular characterizations of avian influenza viruses isolated from humans. In order to make the bioinformatical studies on avian influenza more efficient, it is necessary to build an avian influenza information platform.
     In this article, data from international canonical database ISD and IVR of NCBI were downloaded to build a local database FLU-KEY by Python, CGI technology. Based on this database, a web search system was built using HTML, Python and CGI. Specially, a new search method was developed by which researchers could get and download virus data ( fasta format ) including all six internal proteins.
     In host transmission section, a method developed by Dr. Kou was used to make a classification machine which can indicate whether the virus could transmit from avian to human. First, wavelet packet decomposition was done on the new virus genome sequence to get the energy quantities. Then KNN method was used to calculate the Euclidean distances and determine whether the virus could transmit from avian to human. Last, this classification machine was combined to the avian influenza information platform by Biopython module and PyWavelets Module of Python.
     Using this platform, researchers could not only search and download avian influenza data to do bioinformatical research, but also do analysis and prediction to know whether a new virus has the characteristic of host transmission.
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