Abstract
Properly performed, biomarker discovery can lead to effective candidates that can ultimately serve as predictors of disease, medical condition, define therapeutic parameters, and many other applications in medicine. Preferably, biomarkers comprise a panel of indicators, e.g. proteins and/or peptides that can be predictive or diagnostic of the medical condition of interest. Emphasis here is placed on “panel,” as single candidates are rarely sufficient to provide the necessary sensitivity and specificity. To develop an effective panel that survives the development process described in Chap. 19, proper experimental design and attention to important statistical parameters are critical to ensure success. Errors in discovery can lead to an inefficient use of expensive resources, as these may not be uncovered until the latter stages in biomarker development. Hence, accuracy, precision, and an estimate of the power of the proposed analyses are critical in the discovery of the panel of candidate biomarkers by proteomic methods, as is the selection of statistical approaches to refine and appropriately reduce the dataset for subsequent confirmatory assays.
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Wiktorowicz, J.E., Soman, K.V. (2016). Discovery of Candidate Biomarkers. In: Mirzaei, H., Carrasco, M. (eds) Modern Proteomics – Sample Preparation, Analysis and Practical Applications. Advances in Experimental Medicine and Biology, vol 919. Springer, Cham. https://doi.org/10.1007/978-3-319-41448-5_21
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