@article {bioinflmu-513,
	title = {{BioWeka--extending the Weka framework for bioinformatics}},
	journal = {Bioinformatics},
	volume = {23},
	number = {5},
	year = {2007},
	pages = {651-653},
	abstract = {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{\textquoteright}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. Availability: The software,

documentation and tutorial are available at http://www.bioweka.org.},
	doi = {10.1093/bioinformatics/btl671},
	author = {Jan Erik Gewehr and Martin Szugat and Ralf Zimmer}
}