Home // IMMM 2012, The Second International Conference on Advances in Information Mining and Management // View article
Authors:
Olgierd Unold
Keywords: Amyloid Proteins; Data Mining; Feature Subset Selection
Abstract:
In this paper, we address the problem of predicting the location of amyloidogenic regions in proteins. To support this process we used a genetic algorithm-based wrapper feature subset selection. The wrapper feature subset selection approach is about choosing a minimal subset of features that satisfies an evaluation criterion. We find that most of the machine learning algorithms taken from the WEKA software achieved no worse Accuracy over reduced dataset than over the non-reduced dataset. Moreover, research has confirmed the observations of other researchers, that amino-acids have highly position-dependent propensities.
Pages: 37 to 40
Copyright: Copyright (c) IARIA, 2012
Publication date: October 21, 2012
Published in: conference
ISSN: 2326-9332
ISBN: 978-1-61208-227-1
Location: Venice, Italy
Dates: from October 21, 2012 to October 26, 2012