Journal of Advances in Information Technology (JAIT)
@article{AltartouriGlasmachers2021,
author = {Altartouri, Haneen and Glasmachers, Tobias},
title = {Improved Protein Function Prediction by Combining Clustering with Ensemble Classification},
journal = {Journal of Advances in Information Technology (JAIT)},
month = {August},
year = {2021},
}
Altartouri, H., & Glasmachers, T.. (2021). Improved Protein Function Prediction by Combining Clustering with Ensemble Classification. Journal of Advances in Information Technology (JAIT).
2020
A Versatile Combination of Classifiers for Protein Function Prediction
The Twelfth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies
@aricle{AltartouriGlasmachers2020,
author = {Altartouri, Haneen and Glasmachers, Tobias},
title = {A Versatile Combination of Classifiers for Protein Function Prediction},
year = {2020},
}
Altartouri, H., & Glasmachers, T.. (2020). A Versatile Combination of Classifiers for Protein Function Prediction. The Twelfth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies.
2019
Moment Vector Encoding of Protein Sequences for Supervised Classification
In Practical Applications of Computational Biology and Bioinformatics, 13th International Conference (pp. 25–35) Springer International Publishing
@incollection{AltartouriGlasmachers2019,
author = {Altartouri, Haneen and Glasmachers, Tobias},
title = {Moment Vector Encoding of Protein Sequences for Supervised Classification},
booktitle = {Practical Applications of Computational Biology and Bioinformatics, 13th International Conference},
pages = {25–35},
publisher = {Springer International Publishing},
month = {June},
year = {2019},
doi = {10.1007/978-3-030-23873-5_4},
}
Altartouri, H., & Glasmachers, T.. (2019). Moment Vector Encoding of Protein Sequences for Supervised Classification. In Practical Applications of Computational Biology and Bioinformatics, 13th International Conference (pp. 25–35). Springer International Publishing. http://doi.org/10.1007/978-3-030-23873-5_4
The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.
