Maja is the youngest member of the bioinfo group. She has a background in mathematics and has a master degree in molecular biology.
She is involved in several projects researching different scientific topics. As a junior researcher her work was focused on interaction between human microbiome and development of liver cirrhosis. She is currently employed on a project that investigates genomics of basal metazoans. She also takes part in collaboration with Heidelberg University Hospital, revealing the context of HIV-1 integration to human genome.
She has experience in data analysis and application of statistical and machine learning methods in genomics, including data from metagenome sequencing, RNA seq, ChIP seq, DRIP seq, and Oxford Nanopore technologies.
Maja is a teaching assistant in graduate and undergraduate level courses, including Algorithms and Programming, Statistics and Machine Learning, Bioinformatics and Computational genomics.
1. Lucic, B.*, Chen, H.-C.*, Kuzman, M.*, Zorita, E*., Wegner, J., Minnerker, V., Roukos, V., Weng, W., Schmidt, M., Fronza, R., Stadhouders, R., Vlahovicek, K.#, Filion, J. G.#, Lusic, M.# Spatially clustered loci with multiple enhancers are frequent targets of HIV-1. BioRxiv 287896 (2018)
2. Elek A, Kuzman M, Vlahovicek K (2018). coRdon: Codon Usage Analysis and Prediction of Gene Expressivity. https://github.com/BioinfoHR/coRdon, http://bioinfo.hr/software-tools/.
3. Franke, V., Ganesh, S., Karlic, R., Malik, R., Pasulka, J., Horvat, F., Kuzman, M., Fulka, H., Cernohorska, M., Urbanova, J., et al. Long terminal repeats power evolution of genes and gene expression programs in mammalian oocytes and zygotes.- Genome Res. gr.216150.116. (2017)
4. Fabijanić, M., and Vlahoviček, K. Big Data, Evolution, and Metagenomes: Predicting Disease from Gut Microbiota Codon Usage Profiles.- In Data Mining Techniques for the Life Sciences, O. Carugo, and F. Eisenhaber, eds. (Springer New York) (2016), pp. 509–531