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BioWeka—extending the Weka framework for bioinformatics

机译:BioWeka-扩展Weka生物信息学框架

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Summary: Given the growing amount of biological data, data mining methods have become an integral part of bioinformatics research. Unfortunately, standard data mining tools are often not sufficiently equipped for handling raw data such as e.g. amino acid sequences. One popular and freely available framework that contains many well-known data mining algorithms is the Waikato Environment for Knowledge Analysis (Weka). In the BioWeka project, we introduce various input formats for bioinformatics data and bioinformatics methods like alignments to Weka. This allows users to easily combine them with Weka's classification, clustering, validation and visualization facilities on a single platform and therefore reduces the overhead of converting data between different data formats as well as the need to write custom evaluation procedures that can deal with many different programs. We encourage users to participate in this project by adding their own components and data formats to BioWeka.
机译:简介:随着生物数据量的增长,数据挖掘方法已成为生物信息学研究不可或缺的一部分。不幸的是,标准数据挖掘工具通常没有足够的能力来处理诸如氨基酸序列。怀卡托知识分析环境(Weka)是包含许多著名的数据挖掘算法的一种流行且免费的框架。在BioWeka项目中,我们为生物信息学数据和生物信息学方法(例如与Weka的比对)引入了各种输入格式。这使用户可以轻松地将它们与Weka的分类,群集,验证和可视化功能结合在一个平台上,从而减少了在不同数据格式之间转换数据的开销,以及减少了编写可处理许多不同程序的自定义评估程序的需要。 。我们鼓励用户通过向BioWeka添加自己的组件和数据格式来参与该项目。

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