Bioinformatics And Computational Biology
At the Biochemistry department office
Appointment on Visitation important
Topic: Cancer Biomaker Discovery
Description: An understanding of molecular mechanisms of cancer is necessary for the identification of biomarkers of diagnostic and/or prognostic value. The application of high-throughput genomic technologies – whole and exome sequencing, transcriptome sequencing, genome-wide methylation analysis and microarray analysis – has made it possible to generate different types of data that can be integrated to decipher these mechanisms. These technologies, however, generate very large volume of data, making it difficult to extract genes that confer special growth and survival advantage to tumour cells.Lack of reproducibility has hindered the transition of biomarkers of diagnostic or prognostic importance into clinical use. Due to the high level of noise in high-throughput data, there is need to incorporate findings from traditional molecular biology studies into the analysis of high-throughput data to generate reliable and reproducible biomarkers. My current research focus is centered on the generation and translation of high-quality biomarkers into the clinic by bridging the gap between molecular biology and cancer genomics.
|1.||Ph.D (Bioinformatics)||South African National Bioinformatics Institute, University of the Western Cape||2015|
Development of tools for precision medicine in cancer
Cancer is a group of diseases that arises from irreversible genomic and epigenomicalterations that result in unrestrained proliferation of abnormal cells. Detailed un-derstanding of the molecular mechanisms underlying a cancer would aid the identi-fication of most, if not all, genes responsible for its progression and the developmentof molecularly targeted chemotherapy. The challenge of recurrence after treatmentshows that our understanding of cancer mechanisms is still poor. As a contribution toovercoming this challenge, an integrative multi-omic analysis on glioblastoma multiforme (GBM) for which large data sets on different classes of genomic and epigenomic alterations have been made available in the Cancer Genome Atlas data portal. The first part of this study will involve protein network analysis for the elucidation of GBM tumourigenic molecular mechanisms, identification of driver genes, prioritisation of genes in chromosomal regions with copy number alteration, and co-expression and transcriptional analysis. The second part will identify differentially expressed miRNAs for which target genes associiiated with the protein network are also differentially expressed. miRNAs and target genes will be prioritised based on the number of targeted genes and targeting miR-NAs, respectively. miRNAs that correlate with time to progression will be selected by an elastic net-penalized Cox regression model for survival analysis. The survival prediction of the selected miRNAs will be determined.
FATAI AZEEZ is a Lecturer II at the Department of Biochemistry
FATAI has a Ph.D in Bioinformatics from South African National Bioinformatics Institute, University of the Western Cape