Abstract
Biomarkers are molecular parameters associated with presence and severity of specific disease states. Search for biological markers of cancer in proteomic profiles is a relatively new but very active research area. This paper presents a novel approach to feature selection and thus biomarker identification. The proposed method is based on blind separation of sources and selection of features from a reduced set of components.
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CITATION STYLE
Boratyn, G. M., Smolinski, T. G., Zurada, J. M., Milanova, M., Bhattacharyya, S., & Suva, L. J. (2004). Hybridization of blind source separation and rough sets for proteomic biomarker identification. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3070, pp. 486–491). Springer Verlag. https://doi.org/10.1007/978-3-540-24844-6_72
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