Data Mining for Cancer Biomarkers with Raman Spectroscopy

Michael B. Fenn () and Vijay Pappu ()
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Michael B. Fenn: University of Florida
Vijay Pappu: University of Florida

Chapter Chapter 8 in Data Mining for Biomarker Discovery, 2012, pp 143-168 from Springer

Abstract: Abstract Raman spectroscopy has the potential to play an important role in the diagnosis and treatment of cancer as a unique type of biomarker technology. Raman spectra can provide a collective picture of the overall composition of biological samples as well as highly sensitive, targeting of specific biomolecular moieties depending upon the application. In the field of Oncology, Raman Spectroscopy can help in the identification of biomarkers for use in drug discovery, cancer-risk assessment, histopathology, and in vivo clinical applications. Continued advancements to data analysis techniques could prove vital in realization of such biomedical applications. This chapter provides a brief overview of some of the more common data analysis methods as well as outlines several of the technical challenges encountered in the implementation of these methods. The development of standardized data techniques with incorporation into fully functional integrated software platforms will also be necessary for clinical applications in future.

Keywords: Raman Spectra; Data analysis; Oncology; Biomarkers; PCA; SVM; LDA; k-means Clustering (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-2107-8_8

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