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A Java framework for statistical analysis and classification of biological sequences
Sequence analysis is one of the major subjects of bioinformatics. Several existing libraries combine the representation of biological sequences with exact and approximate pattern matching as well as alignment algorithms. We present Jstacs, an open source Java library, which focuses on the statistical analysis of biological sequences instead. Jstacs comprises an efficient representation of sequence data and provides implementations of many statistical models with generative and discriminative approaches for parameter learning. Using Jstacs, classifiers can be assessed and compared on test datasets or by cross-validation experiments evaluating several performance measures. Due to its strictly object-oriented design Jstacs is easy to use and readily extensible.
Jstacs is a joint project of the groups Bioinformatics and Pattern Recognition and Bioinformatics at the Institute of Computer Science of Martin Luther University Halle-Wittenberg and the Research Group Data Inspection at the Leibniz Institute of Plant Genetics and Crop Plant Research.
Jstacs is listed in the machine learning open-source software (mloss) repository.
Licensing Information
Jstacs is free software: you can redistribute it and/or modify under the terms of the GNU General Public License version 3 or (at your option) any later version as published by the Free Software Foundation.
Current release
You can download Jstacs version 2.0 here.
You find an overview of the new features in the Recent changes.
We also provide an API documentation and a Cookbook for this release.
Applications
Applications currently using Jstacs:
Bug reports & Feature requests
You can submit bug reports and feature requests via the Jstacs trac or by mail to jstacs@informatik.uni-halle.de. Before you open a new bug ticket, please check if that bug has already been submitted in the list of existing tickets.
In the Jstacs trac, we also provide a forum for discussions about Jstacs.
Latest Paper
The paper Exploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models has been published in Bioinformatics.
Further papers and projects can be found under Projects.
Workshop
The first Jstacs workshop has been held on May, 19th in room 5.09 at the Institute of Computer Science at Martin Luther University Halle. Besides a general introduction to Jstacs, information on new features of Jstacs 1.5, and talks of Jstacs users, we had a discussion on future directions of Jstacs. More details on the program can be found here.
