Achcar Fiona, Camadro Jean-Michel, Mestivier Denis
Modeling in Integrative Biology Group, Jacques Monod Institute, UMR7592 CNRS and Univ Paris-Diderot, Bâtiment Buffon, 15 rue Hélène Brion, 75205 Paris Cedex 13, France.
Nucleic Acids Res. 2009 Jul;37(Web Server issue):W63-7. doi: 10.1093/nar/gkp430. Epub 2009 May 27.
Recently, several theoretical and applied studies have shown that unsupervised Bayesian classification systems are of particular relevance for biological studies. However, these systems have not yet fully reached the biological community mainly because there are few freely available dedicated computer programs, and Bayesian clustering algorithms are known to be time consuming, which limits their usefulness when using personal computers. To overcome these limitations, we developed AutoClass@IJM, a computational resource with a web interface to AutoClass, a powerful unsupervised Bayesian classification system developed by the Ames Research Center at N.A.S.A. AutoClass has many powerful features with broad applications in biological sciences: (i) it determines the number of classes automatically, (ii) it allows the user to mix discrete and real valued data, (iii) it handles missing values. End users upload their data sets through our web interface; computations are then queued in our cluster server. When the clustering is completed, an URL to the results is sent back to the user by e-mail. AutoClass@IJM is freely available at: http://ytat2.ijm.univ-paris-diderot.fr/AutoclassAtIJM.html.
最近，一些理论和应用研究表明，无监督贝叶斯分类系统在生物学研究中具有特殊的相关性。然而，这些系统尚未完全被生物学界所采用，主要原因是很少有免费的专用计算机程序，而且贝叶斯聚类算法已知耗时较长，这限制了它们在使用个人计算机时的实用性。为了克服这些限制，我们开发了AutoClass@IJM，这是一种具有网络界面的计算资源，可连接到由美国国家航空航天局艾姆斯研究中心开发的强大无监督贝叶斯分类系统AutoClass。AutoClass具有许多强大功能，在生物科学中有着广泛应用：（i）它能自动确定类别数量，（ii）它允许用户混合离散和实值数据，（iii）它能处理缺失值。终端用户通过我们的网络界面上传他们的数据集；然后计算任务会在我们的集群服务器中排队。聚类完成后，结果的URL会通过电子邮件发送回用户。AutoClass@IJM可在以下网址免费获取：http://ytat2.ijm.univ-paris-diderot.fr/AutoclassAtIJM.html 。
