Jstacs: a java framework for statistical analysis and classification of biological sequences

Authors:
Jan Grau;Jens Keilwagen;André Gohr;Berit Haldemann;Stefan Posch;Ivo Grosse
Affiliations:
Institute of Computer Science, Martin Luther University Halle–Wittenberg, Halle, Germany;Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany;Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany;Department of Computer Science, Humboldt University of Berlin, Berlin, Germany;Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany;Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany
Venue:
The Journal of Machine Learning Research
Year:
2012

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Abstract

Jstacs is an object-oriented Java library for analysing and classifying sequence data, which emerged from the need for a standardized implementation of statistical models, learning principles, classifiers, and performance measures. In Jstacs, these components can be used, combined, and extended easily, which allows for a direct comparison of different approaches and fosters the development of new components. Jstacs is especially tailored to biological sequence data, but is also applicable to general discrete and continuous data. Jstacs is freely available at http://www.jstacs.de under the GNU GPL license including an API documentation, a cookbook, and code examples.