EP 64: Machine Learning and Mutli-Omics Data with Mxolisi Nene
From the bioinformatics lab by The Bioinformatics Lab
November 20, 2025 · 59 min
About this episode
Mxolisi Nene discusses his journey into bioinformatics and the integration of multi-omics data with machine learning.
In this episode of the Bioinformatics Lab Podcast, Mxolisi Nene shares his journey from a curious kid “scanning soil” with a stick and a broken Pentium II in rural KwaZulu-Natal to a bioinformatician and PhD candidate at the Agricultural Research Council in Pretoria. He walks through his path from animal science into bioinformatics, profiling the gut microbiomes of indigenous village chickens using 16S and metagenomic sequencing, and how wrestling with messy real-world data led him into multi-omics integration and machine learning. Mxolisi explains concepts like feature engineering, neural networks, and ecological “tipping points” in soil ecosystems—showing how combining metagenomic, metabolomic, proteomic, and genomic layers can help predict when an environment is on the brink of collapse, with implications for agriculture, food security, and even disease research. We also dig into the philosophical side of his work: why the explosion of public omics data makes it almost a moral obligation to use these tools for better outbreak prevention and environmental stewardship, how conferences like PHA4GE in Cape Town and the AI working group are quietly seeding a new generation of…
People in this episode
Host: The Bioinformatics Lab
Guest: Mxolisi Nene
Topics covered
- machine learning
- multi-omics integration
- bioinformatics
- gut microbiomes
- environmental stewardship
- agriculture
- data science
Keywords
- bioinformatics
- machine learning
- multi-omics
- gut microbiomes
- metagenomic sequencing
- feature engineering
- neural networks
- ecological tipping points
- agriculture
- food security
Mentioned in this episode
Organizations: Agricultural Research Council
Places: KwaZulu-Natal, Pretoria, Cape Town
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