Statistical modelling of natural selection based on deoxyribonucleic acid (DNA) data is the research field that primarily interests me. Molecular evolutionary studies offer effective methods for using DNA genomic information to investigate biomedical phenomena. Phylogenetics – the study of the evolutionary relationships among living organisms using genetic data – is one of those methods. Natural selection is an aspect of phylogenetics that has gained significant research attention. It includes the use of theoretical probability techniques to identify genetic loci that are crucial to the survival of living organisms. One utility of natural selection analyses is in the understanding of how pathogens evade treatments and the immunity of their hosts. Given the lack of cure for some existing pathogens such as HIV and the continuous outbreaks of new pathogens such as the coronavirus, natural selection remains an ever exciting research field. Selection has traditionally been studied as a measure of relative fitness among alleles in the field of population genomics. As a result, there exists a good volume of theoretical work in the population genomics literature. This rich body of work is yet to be fully synchronised with phylogenetic research due to mathematical complexities. Therefore, I am specifically keen on bridging the gap between the population genomic and phylogenetic fields with respect to Darwinian natural selection.
2014 - Present: Ordinary Member.
South African Statistical Association
2024 - Present: Academic Member.
South African Society for Bioinformatics
2022: 63rd South African Statistical Association Annual Conference
Title: difFUBAR – A Scalable Bayesian Comparison of Selection Pressure (Oral).
Venue: George, Western Cape, South Africa.
2017: 24th HIV Dynamics & Evolution Meeting
Title: Assessing the Robustness of Phylogenetic Models to Changes in Selection Pressures Over Time: A Simulation Study (Poster).
Venue: Sabhal Mòr Ostaig, Sleat, Isle of Skye, Scotland, United Kingdom.
2016: 58th South African Statistical Association Annual Conference
Title: Assessing the Robustness of Phylogenetic Models to Changes in Selection Pressures Over Time: A Simulation Study (Oral).
Venue: University of Cape Town, South Africa.
2014: 56th South African Statistical Association Annual Conference
Title: A Topic Model Approach to Inferring Episodic Directional Selection in Protein Coding Sequences (Oral).
Venue: Rhodes University, Grahamstown, South Africa.
2013: 55th South African Statistical Association Annual Conference
Title: Start-up Designs in Medical Trials (Oral).
Venue: University of Limpopo, South Africa.
2022: C1 Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Sweden.
Host: Dr Ben Murrell.
2018: School of Medicine, University of California, San Diego.
Host: Dr Ben Murrell.
2022: University Capacity Development Programme – Mobility Grant (Value: 50,000.00 ZAR)
The National Graduate Academy for Mathematical and Statistical Sciences, South Africa.
2021: Subcommittee A Research Grant (Value: 50,000.00 ZAR)
Faculty of Economic & Management Sciences, Stellenbosch University, South Africa.
2021: Matthew David Zackey and Jana van Tonder (Honours)
Title: Client Selection for Marketing using Tree Ensemble Methods.
Stellenbosch University, South Africa.
2024: Merwe Engelbrecht and Christopher Paul (Honours)
Title: Classification Models Determining Queen Bee Status Among Hives Using Audio Data.
Stellenbosch University, South Africa.
[1] H. Sadiq and D. P. Martin, “scoup: Simulate Codons with Darwinian Selection Incorporated as as Ornstein-Uhlenbeck Process,” Journal of Open Source Software, 11(119):9797, 2026. https://doi.org/10.21105/joss.09797.
[2] H. Sadiq, P. Truong, M. Danielsson, V. Kumar, H. N. Nordlinder, D. P. Martin, and B. Murrell, “difFUBAR: Scalable Bayesian Comparison of Adaptive Evolution,” bioRxiv, 2025. doi.org/10.1101/2025.05.19.654647.
[3] H. Sadiq, “scoup: Simulate Codons with Darwinian Selection Incorporated as as Ornstein-Uhlenbeck Process,” R Package, Bioconductor, 2024. https://doi.org/10.18129/B9.bioc.scoup.
[4] H. Sadiq, “A Topic Model Based Approach to Inferring Episodic Directional Selection in Protein Coding Sequences,” Master’s thesis, University of Cape Town, South Africa, 2015. http://hdl.handle.net/11427/20013.