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Current research interests of the GenomeDataLab are organized into four themes:
[1]
genomics of DNA repair
We aim to understand mechanisms of maintaining genome integrity in human cells via statistical analyses of mutation patterns in cancer.
an example publication:
DNA mismatch repair promotes APOBEC3-mediated diffuse hypermutation in human cancers
D Mas-Ponte, F Supek (2020) Nature Genetics.
[2]
mRNA quality control
We are interested in how the pathways dealing with synthesis and turnover of messenger RNAs shape genomes and transcriptomes, in health and disease.
an example publication:
The impact of nonsense-mediated mRNA decay on genetic disease, gene editing and cancer immunotherapy
RGH Lindeboom, M Vermeulen, B Lehner, F Supek (2019) Nature Genetics
"An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem." -- John Tukey
[3]
predicting cancer evolution
Combining experiment and genomics, we scan cancer genomes for causal genes and for genetic interactions to better understand tumor evolution.
an example publication:
Loss of the abasic site sensor HMCES is synthetic lethal with the activity of the APOBEC3A cytosine deaminase in cancer cells
J Biayna, I Garcia-Cao, ..., F Supek*, T Stracker* (2021) PLOS Biology
[4]
bioinformatics of gene function
From E. coli to human genome, the function of a substantial fraction of the genes is unknown; we think that machine learning approaches can help solve this.
an example publication:
The landscape of microbial phenotypic traits and associated genes. M Brbić, M Piškorec, V Vidulin, A Kriško, T Šmuc, F Supek (2016) Nucl Acids Res.
"The best thing about being a statistician is that you get to play in everyone's backyard." -- John Tukey.
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