SLIIT Journal of Humanities and Sciences [SJHS]

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/2238

Browse

Filters

2022 - 20242

Advanced Search

Filter by

Settings

Author: search.filters.author.Jayatillake, R.

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationOpen 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.
  • Thumbnail Image
    PublicationOpen Access
    Determining Differentially Expressed Genes in Dengue Patients During Disease Progression
    (Faculty of Humanities and Sciences, SLIIT, 2024-05-15) Coorey, H.; Jayatillake, R.; Jayathilaka, N.; Ambanpola, N.
    Gene expression studies on gene transcription to synthesize functional gene products have been used extensively to understand biological differences between different disease conditions. Thus, this study determines differentially expressed genes in dengue infection during disease progression following the three phases: Febrile, Defervescence and Convalescent. Integrative data analysis of two publicly available longitudinal datasets in Gene Expression Omnibus (GEO) database has been employed to accomplish the prime objective of exploring temporal gene expression patterns. The Friedman test was given more emphasis due to the non-normality distributions of data. Repeated measures analysis of variance (ANOVA) and linear mixed models were also implemented to examine the potential of detecting differentially expressed genes despite non-normality. The Friedman test revealed significant differences in gene expression levels across different phases in dengue disease over time. This led to a notably higher count of genes showing differential expression compared to the other two methods: Repeated measures ANOVA and linear mixed models. The pathway analysis approach consists of significant differentially expressed genes derived from the Friedman test. The results identified upregulated pathways with any significant change in the overall expression of genes within pathways over time for the Febrile and Defervescence phases considering the Convalescent phase as a baseline. Moreover, genes available in pathways were not identified by the two parametric tests for non-normal data implying that the parametric approaches resulted in the least significance for data with non-normal distributions.