Research Interests

Computational molecular biology

Discrete and convex optimization

Linear programming

3D computer graphics

Degrees

MSc in mathematics, Mathematics and Computer Science, Department of Mathematics, University of Osijek, Croatia, 2021.

BSc in Mathematics, Department of Mathematics, University of Osijek, Croatia, 2018.

Publications

1. B. Borozan, L. Borozan, D. Ševerdija, F. Rojas Ringeling, D. Matijević, Optimal Marker Genes for c-Separated Cell Types, RECOMB 2025, Seoul, Republika Koreja, 2025
   Abstract

   The identification of cell types in single-cell RNA-seq studies relies on the distinct expression signature of marker genes. A small set of target genes is also needed to design probes for targeted spatial transcriptomics experiments and to target proteins in single-cell spatial proteomics or for cell sorting. While traditional approaches have relied on testing one gene at a time for differential expression between a given cell type and the rest, more recent methods have highlighted the benefits of a joint selection of markers that together distinguish all pairs of cell types simultaneously. However, existing methods either impose constraints on all pairs of individual cells which becomes intractable even for medium-sized datasets, or ignore intra-cell type expression variation entirely by collapsing all cells of a given type to a single representative. Here we address these limitations and propose to find a small set of genes such that cell types are c-separated in the selected dimensions, a notion introduced previously in learning a mixture of Gaussians. To this end, we formulate a linear program that naturally takes into account expression variation within cell types without including each pair of individual cells in the model, leading to a highly stable set of marker genes that allow to accurately discriminate between cell types and that can be computed to optimality efficiently.
2. B. Borozan, L. Borozan, D. Ševerdija, D. Matijević, S. Canzar, Fortuna Detects Novel Splicing in Drosophila scRNASeq Data, ICT and Electronics Convention (MIPRO), 2023 46th MIPRO, Opatija, Hrvatska, 2023, 410-415
   Abstract

   Recent developments in single-cell RNA sequencing techniques (scRNASeq) have made large quantities of sequenced data available across numerous species and tissues. Alternative splicing (AS) of pre-mRNA introns varies between tissues and even between cell-types and can be altered in disease. The study of novel AS, using standard RNASeq data, has been extensively studied for many years, while similar work on scRNASeq data has been scarce, despite its potential to offer a broader insight into cell-type specific processes. In this paper, we propose a novel pipeline that uses fortuna, a method that efficiently classifies and quantifies novel AS events, to process scRNASeq samples. Due to its short lifespan, high number of progeny, low maintenance cost, and intricate alternative splicing patterns similar in complexity to those of mammals, Drosophila Melanogaster (fruit fly) is a species of particular interest to researchers. Therefore, we experimentally evaluate our pipeline on real-world Drosophila single-cell data samples from the Fly Cell Atlas.

Teaching

Konzultacije (Office Hours): Po dogovoru.

Personal

Birthplace: Osijek