Team
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Paolo Marcatili, PhD, Associate Professor
I am a bioinformatician and computational biologist with an extensive expertise in the following areas: - Structural Bioinformatics - Machine Learning - Immunological Bioinformatics - Immunotherapy I have a background in programming, robotics, control and systems theory, and a deep understanding of biology and immunology. I am excited by anything that combines 2 or more of the following things: immunology, machine learning, protein structure prediction, obscure avantgard art, fancy cocktails. Probably not in this order.
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Anna-Lisa Schaap-Johansen, PhD student
Bioinformatician with a background in omics, Biochemistry, Molecularbiology and Chemistry. My latest research involved biomarker discovery for skin cancer, specifically Acral Lentiginous Melanoma, done using multiomics data. The work was conducted on Chinese patients, and was a collaboration between China and Denmark. My current research goal is to combine Deep Learning and Immunology to improve neoepitope prediction. This research will involve multiomics data and the combination of the data to strengthen prediction. This work will hopefully improve immunotherapy and enable us to cure cancer even at late stages.
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Milena Vujovic, PhD student
Former chemist, aspiring bioinformatician. Currently applying my diverging mix of skills behind a computer screen, day by day more entangled in deciphering immunological abbreviations, all the while trying to understand T cell receptor repertoires. My PhD project “Statistical Modelling of TCR Repertoires for Immunotherapy and Drug Delievery” is concerned with understanding tumour-immunity interactions. Particularly I’m interested in illuminating mechanisms of epitope spreading utilising high-throughput sequencing data and constructing statistical models of T-cell receptor repertoires. The final goal is attempting a framework for rational selection of combination therapy by interpreting cancer immunity in individuals, thus taking the next step in personalized medicine.