Costa, E.P. and Lorena, A.C. and Carvalho, A.C.P.L.F. and Freitas, A.A. (2008) Top-down hierarchical ensembles of classifiers for predicting G-Protein-Coupled-Receptor functions. In: Advances in Bioinformatics and Computational Biology (Proc. 2008 Brazilian Symposium in Bioinformatics (BSB-2008)), Lecture Notes in Bioinformatics 5167, Aug 28-30, 2008, Santo Andre, Brazil.
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Despite the recent advances in Molecular Biology, the function of a large amount of proteins is still unknown. An approach that can be used in the prediction of a protein function consists of searching against secondary databases, also known as signature databases. Different strategies can be applied to use protein signatures in the prediction of function of proteins. A sophisticated approach consists of inducing a classification model for this prediction. This paper applies five hierarchical classification methods based on the standard Top-Down approach and one hierarchical classification method based on a new approach named Top-Down Ensembles - based on the hierarchical combination of classifiers - to three different protein functional classification datasets that employ protein signatures. The algorithm based on the Top-Down Ensembles approach presented slightly better results than the other algorithms, indicating that combinations of classifiers can improve the performance of hierarchical classification models.
|Item Type:||Conference or workshop item (Paper)|
|Uncontrolled keywords:||classification, bioinformatics|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group|
|Depositing User:||Mark Wheadon|
|Date Deposited:||29 Mar 2010 12:12|
|Last Modified:||29 Mar 2010 12:12|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/24052 (The current URI for this page, for reference purposes)|
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