Browsing by Author "Bendou, Hocine"

Now showing 1 - 9 of 9
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    Baobab LIMS: An open source biobank laboratory information management system for resource-limited settings
    (University of the Western Cape, 2019) Bendou, Hocine; Christoffels, Alan
    A 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.
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    Computational analysis of multi-omic data for the elucidation of molecular mechanisms of neuroblastoma
    (University of Western Cape, 2021) Giwa, Abdulazeez; Bendou, Hocine
    Neuroblastoma 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.
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    Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics
    (Springer Nature, 2018) Baichoo, Shakuntala; Bendou, Hocine; de Beste, Eugene; Yi, Long
    Background: The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging. Results: H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community. Conclusion: The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network.
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    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, Hocine
    Background: 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.
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    Evaluation of protein purification techniques and effects of storage duration on lc-ms/ms analysis of archived ffpe human crc tissues
    (Frontiers Media, 2021) Rossouw, Sophia C.; Bendou, Hocine; Blignaut, Renette J.
    To elucidate cancer pathogenesis and its mechanisms at the molecular level, the collecting and characterization of large individual patient tissue cohorts are required. Since most pathology institutes routinely preserve biopsy tissues by standardized methods of formalin fixation and paraffin embedment, these archived FFPE tissues are important collections of pathology material that include patient metadata, such as medical history and treatments. FFPE blocks can be stored under ambient conditions for decades, while retaining cellular morphology, due to modifications induced by formalin. However, the effect of long-term storage, at resource-limited institutions in developing countries, on extractable protein quantity/quality has not yet been investigated. In addition, the optimal sample preparation techniques required for accurate and reproducible results from label-free LC-MS/MS analysis across block ages remains unclear. This study investigated protein extraction efficiency of 1, 5, and 10-year old human colorectal carcinoma resection tissue and assessed three different gel-free protein purification methods for label-free LC-MS/MS analysis. A sample size of n 17 patients per experimental group (with experiment power 0.7 and α 0.05, resulting in 70% confidence level) was selected.
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    From biobanking to bioinformatics
    (Universty of the Western Cape, 2018) Bendou, Hocine
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    Identification of insertion-induced enhancers linked to gene drivers within non-coding DNA using a pipeline for diffuse large b-cell lymphoma H3K27ac ChIP-seq data
    (University of the Western Cape, 2022) Jassiem, Wardah; Bendou, Hocine
    Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL) and incorporates a diverse range of illnesses with varying biology, clinical manifestations, and therapeutic responses. Functional insertion mutations represent the driving mechanism behind many oncologic illnesses. Research has shown that variants associated with cancer in the non-coding portion of the genome, which is enriched with enhancer elements, is greatly underappreciated. The present study designed a bioinformatics pipeline using Nextflow DSL2 to identify insertion-induced enhancers associated with DLBCL oncogenes within the non-coding genome using H3K27ac ChIP-seq data. Gapped DLBCL reads identified by bowtie were mapped to the human reference genome with bowtie2. Non-coding insertions were identified with BEDTools and verified by pBla.
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    Novel genomic biomarkers for pediatric and adult acute myeloid leukemia
    (University of the Western Cape, 2023) Bendou, Hocine; Eshibona, Nasr O M
    Acute 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.
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    Reconstruction of gene regulatory networks of inflammation-associated genes in different clinical stages of diffuse large B-cell lymphoma
    (University of the Western Cape, 2022) Mfuphi, Nomlindelo Witness; Bendou, Hocine
    Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignancy that is driven by complex gene regulatory networks (GRNs). Numerous genes exert distinct effects on the progression and therapeutic outcome of DLBCL. Previous studies have associated DLBCL with inflammation but the GRNs involved in this mechanism have not yet been explored. The objectives of this current study are to reconstruct inflammation-associated networks and to understand the effects of inflammation on the pathogenesis and progression of DLBCL in different clinical stages.