Abstract
Osteogenesis Imperfecta (OI) is a genetic collagenous disease caused by mutations in one or both of the genes COLIA1 and COLIA2. There are at least four known phenotypes of OI, of which type II is the severest and often lethal. We applied a noise correction mechanism called polishing to a data set of amino acid sequences and associated information of point mutations of COLIA1. Polishing makes use of the inter-relationship between attribute and class values in the data set to identify and selectively correct components that are noisy. Preliminary results suggest that polishing is a viable mechanism for improving data quality, resulting in a more accurate classification of the lethal OI phenotype.
This work was supported by NASA NCC2-1239 and ONR N00014-03-1-0516.
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Teng, C.M. (2003). Noise Correction in Genomic Data. In: Liu, J., Cheung, Ym., Yin, H. (eds) Intelligent Data Engineering and Automated Learning. IDEAL 2003. Lecture Notes in Computer Science, vol 2690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_8
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