Trainees
Ashley Ehlers
Ph.D. Bioinformatics and Computational Biology
E-mail: [email protected]
Ashley's PhD project focuses on building and grokking a machine learning framework for predictive modelling of diseases using large omics data sets. The analysis of omics data remains complex and fraught with potential for misinterpretation. Ashley is particularly interested in the design of best practices for an end-to-end optimal performing and updated machine learning framework for suitable biosignature identification using gene expression profiling and proteomics data sets. These biosignatures are not only useful in identifying the gene or protein sets for predictive modelling but can also shed light on the biological processes involved which improves our understanding of the domain.
Kimberly Coetzer
Ph.D. Bioinformatics and Computational Biology
E-mail: [email protected]
Kimberly is currently in her first year of PhD under the supervision of Professor Gerard Tromp and Professor Gian Van der Spuy. Kimberly is interested in integrative research involving multi-omics data and how the findings might be used to better understand genetic disorders. Her research will focus on the proteogenomics of genetic disorders, specifically amyotrophic lateral sclerosis (ALS). The aim of this PhD is to develop a containerized tool for reproducible proteogenomic data analysis using WGS, RNA-Seq and proteomics data. The results will be used to gain biological insight into ALS by analyzing disease mechanisms and gene functions. Kimberly plans to use the skills gained through her PhD to pursue a career as a full-time bioinformatician.
Abhinav Sharma
Ph.D. Molecular Biology
E-mail: [email protected]
Abhinav holds a masters degree in computer science and has extensive experience in developing software for bioinfromatics. His PhD project is focused on creating a new generation of MTb-specific and sequencing technology-independent tools for analyzing WGS data using modern machine learning techniques (i) for genome alignment (ii) for variant calling and (iii) to combine heterogenous machine learning models for resistance prediction, to achieve comparable performance against the state-of-the-art tools.
Chipo Manda
M.Sc. Molecular Biology
E-mail: [email protected]
Chipo’s MSc project focuses on developing a preprocessing workflow with a containerized pipeline for studying bacterial gene expression. The main objective of her project is to compare two containerized computational pipelines for the preprocessing of bacterial RNA-seq data. Specifically, she uses the nf-core RNA-seq and ProkSeq pipelines, analysing their outputs, and evaluating their performance in terms of computational resources and time required. Chipo, who is from Zambia, is funded by a DAAD MSc Scholarship.
Cross Disciplinary Students
In addition to our own students, we also co-supervise a number of students based in other research groups, some of whom spend most, or all of their time working in the Bioinformatics section.
Alicen Henning
PhD Human Genetics
[email protected]
Raadhiyah Mathee
Ph.D.. Human Genetics
[email protected]
Stacey Engel
Ph.D.. Molecular Biology (Animal TB)
[email protected]
Lusanda Madula
M.Sc.. Molecular Biology (Parkinsons Disease)
[email protected]
Honours Students
We also supervise several Honours students from both the Division of Molecular Biology & Human Genetics and the Centre for Bioinformatics and Computational Biology.