Research Publications

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4194

This main community comprises five sub-communities, each representing the academic contribution made by SLIIT-affiliated personnel.

Browse

Filters

2017 - 201912020 - 20243

Advanced Search

Filter by

Settings

Has files: YesSubject: search.filters.subject.Dengue

Search Results

Now showing 1 - 4 of 4
  • 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.
  • Thumbnail Image
    PublicationOpen 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.
  • Thumbnail Image
    PublicationEmbargo
    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. G
    This 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.
  • Thumbnail Image
    PublicationEmbargo
    A wireless continuous patient monitoring system for dengue; Wi-Mon
    (Faculty of Graduate Studies and Research, 2017-01-26) Nubenthan, S.; Kanagasabapathy, R.
    The improvements in the wireless networking technologies and the integrated electronic circuits have allowed the advancement in the Wireless Body Area Network. WBAN offers many applications in remote health monitoring and medicine. IEEE 802.15.4j and IEEE 802.15.6 are standards for the medical WBAN. It allows the integration of intelligent and miniaturized sensor nodes in or on a human body to monitor the human body functions. It has great potential to make a huge transformation in the future of medical industry. The WBAN concept provides plentiful new innovative ideas to enhance the health care systems. The paper presents a wireless monitoring system for patients who need continuous monitoring, using WBAN concept. This wireless monitoring system contains sensor network and remote monitoring application. It contributes to collection of the vital information of the patients such as temperature, pulse rate, ECG (electrocardiogram), oxygen saturation and blood pressure. Moreover, the system also provides management of information collected from the sensors, alert the administration in severe condition of the patients. The design and implementation of system are discussed in this paper.