SLIIT International Conference on Advancements in Science and Humanities [SICASH]
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SLIIT International Conference on Advancements in Science and Humanities is organized by the Faculty of Humanities and Sciences of the Sri Lanka Institute of Information Technology (SLIIT), the annual research multi-conference of the faculty.
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Publication Open Access Determining Differentially Expressed Genes in Dengue Patients during Disease Progression(Faculty of Humanities and Sciences, SLIIT, 2023-11-01) 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 the 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 the 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. Since previous studies on gene expression have not primarily relied on normality assumption, repeated measures analysis of variance and linear mixed models were implemented to examine the potential of detecting differentially expressed genes despite non-normality. The Friedman test indicated that gene expression levels differentiate with different phases in dengue disease over time, resulting in a high number of significant differentially expressed genes compared to the other two techniques. The pathway analysis approach consists of significant differentially expressed genes derived from the Friedman test. The results identified 27 and 26 upregulated pathways for the “Febrile and Convalescent” and “Defervescence and Convalescent” groups respectively. 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.Publication Embargo Modeling and Forecasting of the Weekly Incidence of Dengue in Colombo District of Sri Lanka(Faculty of Humanities and Sciences, SLIIT, 2022-09-15) Arachchi, K. A. N. L. K.; Peiris, T. S. GThis study was designed to develop a time series model for the weekly incidence of dengue in the Colombo district of Sri Lanka. Weekly occurrence of dengue fever counts from January 2015 to August 2020 in the Epidemiological Report by the Ministry of Health was used for the study . ARIMA (2,1,0) with the addition of AR (16) was identified as the most effective model. The model was trained using data from January 2015 to December 2019. The balance data was used to validate the model. The residuals of the model satisfied the randomness and constant variance, but the residuals significantly deviated from the normality. The results showed that the forecasted figures were consistent with the observed series. However, a noticeable percentage error was observed sequentially in the late 2020s. Those errors could be attributable to the fact that there was an underreporting of dengue fever cases due to social and operational shocks of the Covid-19 Pandemic.