Scoring-based analysis of protein patterns for identification of myeloma cancer
Conference Paper
Overview
Research
Identity
Additional Document Info
View All
Overview
abstract
Early detection is critical in cancer control and prevention. Proteomics is an area in discovery of biomarkers that are molecular parameters associated with presence and severity of specific disease states. Protein samples are analyzed on the basis of mass to charge ratio (m/z) of particles they are composed of. Sequences of intensities (i.e. number of particles with specific value of m/z) can be interpreted using statistical approaches or information theory and data mining tools. The data mining, statistical, and information theoretical approaches have already been successfully applied to identify several types of cancer in gene or protein samples. This paper presents an application of scoring-based methods for detecting myeloma cancer sites in a sequence of ion intensity values obtained from protein samples. A novel and simple to compute scoring method is also introduced.
