Concepts and applications for influenza antigenic cartography.
Concepts and applications for influenza antigenic cartography.
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DOI：
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发表时间：
2011-05
影响因子：
4.4
通讯作者：
Zhipeng Cai;Tong Zhang;X. Wan
中科院分区：
文献类型：
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作者：
Zhipeng Cai;Tong Zhang;X. Wan
流感抗原制图基于免疫学数据集（例如血凝抑制和微量中和测定）将流感抗原投影到二维或三维图中。一个强大的抗原图谱可以促进流感疫苗株的选择，因为抗原图谱可以通过直观的抗原图谱简化数据解释。然而，由于免疫学数据中嵌入的具有挑战性的特征，例如数据不完整性、高噪声和低反应器，抗原制图构建并不是微不足道的。为了克服这些挑战，我们开发了一种计算方法，时间矩阵完成多维缩放（MC-MDS），通过适应低秩MC的概念，从Netflix的电影推荐系统和MDS方法，从地理制图建设。H3 N2和2009年H1N1流感病毒的应用表明，时间MC-MDS是有效的和高效的流感抗原图谱的构建。该网络服务器可在http://sysbio.cvm.msstate.edu/AntigenMap上获得。
Influenza antigenic cartography projects influenza antigens into a two or three dimensional map based on immunological datasets, such as hemagglutination inhibition and microneutralization assays. A robust antigenic cartography can facilitate influenza vaccine strain selection since the antigenic map can simplify data interpretation through intuitive antigenic map. However, antigenic cartography construction is not trivial due to the challenging features embedded in the immunological data, such as data incompleteness, high noises, and low reactors. To overcome these challenges, we developed a computational method, temporal Matrix Completion-Multidimensional Scaling (MC-MDS), by adapting the low rank MC concept from the movie recommendation system in Netflix and the MDS method from geographic cartography construction. The application on H3N2 and 2009 pandemic H1N1 influenza A viruses demonstrates that temporal MC-MDS is effective and efficient in constructing influenza antigenic cartography. The web sever is available at http://sysbio.cvm.msstate.edu/AntigenMap.