AutoClassWeb：用于贝叶斯聚类的简单Web界面
AutoClassWeb: a simple web interface for Bayesian clustering
摘要：
目的：数据聚类是组学时代常见的探索步骤，特别是在基因组学和蛋白质组学中，许多基因或蛋白质可以从一个或多个实验中量化。贝叶斯聚类是一种功能强大的算法，可以对数千个基因或蛋白质进行分类。AutoClass C，它的原始实现，处理丢失的数据，自动确定最佳数量的集群，但不是user-friendly.Results：我们开发了一个在线工具，称为AutoClassWeb，它提供了一个易于使用的Web界面与AutoClass贝叶斯聚类。输入数据作为TSV文件输入。结果以便于使用电子表格程序或Python或R等编程语言进行进一步分析的格式提供。AutoClassWeb是用Python实现的，并在3-Clauses BSD许可证下发布。源代码可在http：//www.example.com上获得，并附有详细的文档。github.com/pierrepo/autoclassweb
英文摘要：
Objective: Data clustering is a common exploration step in the omics era, notably in genomics and proteomics where many genes or proteins can bequantified from one or more experiments. Bayesian clustering is a powerful algorithm that can classify several thousands of genes or proteins. AutoClass C, its original implementation, handles missing data, automatically determines the best number of clusters but is not user-friendly.Results: We developed an online tool called AutoClassWeb, which provides an easy-to-use web interface for Bayesian clustering with AutoClass. Input data are entered as TSV files. Results are provided in formats that ease further analyses with spreadsheet programs or with programming languages, such as Python or R. AutoClassWeb is implemented in Python and is published under the 3-Clauses BSD license. The source code is available athttps://github.com/pierrepo/autoclassweb along with a detailed documentation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
