BIOINFORMATICS × MACHINE LEARNING
Making sense of
biological
complexity.
I’m Rust Turakulov. I develop analytical tools that turn genomic data into answers.
Melbourne, Australia / Biology. Data. Discovery.
01 / RESEARCH FOCUS
Better questions.
Clearer classifications.
I’m interested in how machine learning can reveal meaningful patterns in disease — from methylation profiles to the microbiome.
Disease classification
with machine learning
Exploring tumor types through DNA methylation, dimensionality reduction and predictive modelling.
Related publicationsThe Bethesda
classifier project
Participation in the Bethesda classifier project at NCI / NIH, alongside work on Methylscape, tumor-classification workflows and research data integration.
My work at NIHGenomics into
working tools
From microbial profiles to sequencing pipelines: building useful, interactive ways to explore complex biological data.
Explore the applications02 / A LITTLE CONTEXT
Biology first.
Curiosity, always.
My career began in the early days of human genome sequencing. It has taken me across research, clinical bioinformatics and software development in Australia and the US.
Today, at AGRF in Melbourne, I develop applications for large microbial datasets. A continuing thread through my work is turning complex data into something people can understand and use.
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