Philosophiae Doctor - PhD (Bioinformatics)
Permanent URI for this collection
Browse
Browsing by Author "Bendou, Hocine"
Now showing 1 - 4 of 4
Results Per Page
Sort Options
Item Baobab LIMS: An open source biobank laboratory information management system for resource-limited settings(University of the Western Cape, 2019) Bendou, Hocine; Christoffels, AlanA laboratory information management system (LIMS) is central to the informatics infrastructure that underlies biobanking activities. To date, a wide range of commercial and open source LIMS are available. The decision to opt for one LIMS over another is often influenced by the needs of the biobank clients and researchers, as well as available financial resources. However, to find a LIMS that incorporates all possible requirements of a biobank may often be a complicated endeavour. The need to implement biobank standard operation procedures as well as stimulate the use of standards for biobank data representation motivated the development of Baobab LIMS, an open source LIMS for Biobanking. Baobab LIMS comprises modules for biospecimen kit assembly, shipping of biospecimen kits, storage management, analysis requests, reporting, and invoicing. Baobab LIMS is based on the Plone web-content management framework, a server-client-based system, whereby the end user is able to access the system securely through the internet on a standard web browser, thereby eliminating the need for standalone installations on all machines. The Baobab LIMS components were tested and evaluated in three human biobanks. The testing of the LIMS modules aided in the mapping of the biobanks requirements to the LIMS functionalities, and furthermore, it helped to reveal new user suggestions, such as the enhancement of the online documentation. The user suggestions are demonstrated to be important for both LIMS strengthen and biobank sustainability. Ultimately, the practical LIMS evaluations showed the ability of Boabab LIMS to be used in the management of human biobanks operations of relatively different biobanking workflows.Item Computational analysis of multi-omic data for the elucidation of molecular mechanisms of neuroblastoma(University of Western Cape, 2021) Giwa, Abdulazeez; Bendou, HocineNeuroblastoma is the most common extracranial solid tumor in childhood. The survival rates of patients with neuroblastoma, especially those in the high-risk category, are still low despite varied therapies. The detailed understanding of the molecular mechanisms underlying the pathogenesis of neuroblastoma is essential to develop better therapeutics and improve the poor survival rates. This study provides a multi-omic analysis of neuroblastoma datasets from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) neuroblastoma project and the Gene Expression Omnibus (GEO) data portals to better understand the molecular mechanisms of neuroblastoma.Item Discovering cancer subtypes by tracking cancer progression with transcriptomic data through the multi-stage process of cancer development.(University of the Western Cape, 2023) Livesey, Michelle Chantel; Bendou, HocineBackground: The development of cancer is driven by genomic alterations, which become more heterogeneous as the disease progresses throughout the stages. Consequently, cancer patients have differential levels of sensitivity to treatment. Tumor heterogeneity thus contributes to therapeutic failure, which ultimately leads to the generally poor prognosis and poor overall survival outcome associated with cancer. Introduction: Transcriptomic profiles can be used to track cancer progression based on gene expression changes that occur throughout the multi-stage process of cancer development. The accumulated genetic changes can be detected when gene expression levels in advanced-stage are less variable but show high variability in early-stage. Normalizing advanced-stage expression samples with early-stage and clustering of the normalized expression samples can reveal cancers with unique gene expression patterns based on cancer progression. Aims: A computational method was employed to investigate cancer progression through RNASeq expression profiles across the multi-stage process of cancer development. The method was assessed in a subtype of the heterogeneous kidney cancer and enabled the discovery of in-depth cancer subtypes based on the differences in gene expression profiles. Methods: A preliminary study was performed by downloading RNA-sequenced gene expression and associated phenotypic and survival profiles of Diffuse Large B-cell Lymphoma, Lung cancer, Liver cancer, Cervical cancer, and Testicular cancer from the UCSC Xena database. Similarly, Kidney renal clear cell carcinoma (KIRC) was downloaded as a validation dataset. Advanced-stage samples were normalized with early-stage to consider heterogeneity differences in the multi-stage cancer progression. The normalized gene expression of the preliminary cancer datasets was subjected to weighted gene co-expression network analysis. Gene modules were linked to cancer-related proteins and pathways using enrichment analyses.Item Novel genomic biomarkers for pediatric and adult acute myeloid leukemia(University of the Western Cape, 2023) Bendou, Hocine; Eshibona, Nasr O MAcute myeloid leukemia (AML) is a heterogeneous type of blood cancer that affects individuals of all ages. AML patients are categorized into favorable, intermediate, and adverse risks based on patients' genomic features and chromosomal abnormalities. Despite this risk stratification, the progression and outcome of the disease remain highly variable in pediatric and adult patients, which emphasizes the importance of finding more accurate genomic biomarkers studying the gene expression profiling of pediatric and adult AML patients to facilitate and improve the risk stratification of the patients. Consequently, two research aims were proposed to study the prognostic heterogeneity for pediatric and adult AML. In pediatric AML, the research project was set to identify a genetic signature related to patients with FLT3-ITD mutation and poor survival. While for adult AML, this study focused on establishing a genetic signature predictive of prognosis with the ability to accurately reclassify the risk of AML intermediate group.