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Publication Open Access Identifying Ordinal Nature Inherited Proteins Associated with a Certain Disease(Faculty of Humanities and Sciences, SLIIT, 2022-10-07) Samarawickrama, O.; Jayatillake, R.; Amaratunga, D.Proteomic studies are studies of protein expression levels. They are growing swiftly with the steady improvement in technology and knowledge of cell biology. Since differentially expressed proteins have an influence on overall cell functionality, this improves discrimination between healthy and diseased states. Identifying prime proteins offers prospective insights for developing optimized and targeted treatments. This research involves analyzing data from an early-stage study of which the main purpose was to identify differentially expressed proteins. There are three progressively serious disease states (healthy to mild to severe) in this study. The analysis can be categorized into 2 stages as univariate and multi-protein analysis. The approach of the univariate analysis was to implement continuation ratio modeling considering one protein at a time to pick those that exhibit potential ordinality. Penalized continuation ratio modeling using lasso regularization incorporated with bootstrapping proteins was performed as the next stage to identify protein combinations that perform well together. Combining results of the univariate and multi-protein analyses identified 20 proteins that join forces to discriminate disease severity with an ordinal setting and 21 proteins that are effective each on its own.Publication Embargo Identifying Proteins Associated with Disease Severity(Faculty of Humanities and Sciences, SLIIT, 2022-09-15) Samarawickrama, O; Jayatillake, R; Amaratunga, DProteomic studies or studies of protein expression levels are growing swiftly with the steady improvement in technology and knowledge on understanding various anomalies affecting humans. Since differentially expressed proteins have an influence on overall cell functionality, this improves discrimination between healthy and diseased states. Identifying prime proteins offers prospective insights for developing optimized and targeted treatment methods. This research involves analyzing data from an early-stage study whose main purpose was to identify differentially expressed proteins. The presence of 3 progressively serious states of disease (healthy to mild to severe) escalates the importance of this study because there is not much research literature that considers ordinal outcomes in studies of this nature. The analysis can be segregated into 2 stages, univariate and multiprotein analysis. Approach of the univariate analysis was to implement continuation ratio model considering one protein at a time to pick those that exhibits potential ordinality. Penalized continuation ratio model using lasso regularization incorporated with bootstrapping proteins was performed as the next stage to identify protein combinations that perform well together. Compound results of the univariate and multi-protein analysis identified 20 most dominant proteins that have the capability to discriminate between the disease states in an ordinal manner satisfactorily.