The Bioinfo team focuses on understanding complex biological questions using genomics and bioinformatics. Through joint projects with fellow experts, we collaborate to develop new methods and gain deeper insights into diverse scientific challenges.
Our research group is committed to advancing the understanding of COVID-19 by investigating the SARS-CoV-2 virus and its interactions with human hosts. We focus on identifying genetic risk factors, exploring viral mutation dynamics, and examining host responses that affect disease severity and progression. Using cutting-edge bioinformatics and high-throughput sequencing technologies, we aim to uncover insights that can inform public health strategies, treatment options, and pandemic preparedness. The recent pandemic highlights the need for interdisciplinary research that integrates genomic, bioinformatic, and clinical data to better understand and manage COVID-19. By analyzing both viral and host genetic factors, our group aims to provide critical insights into the biology of SARS-CoV-2 and its impact on human health, ultimately contributing to improved treatment strategies and more informed public health decisions.
Collaborators: Dubrava University Hospital, the National Forensic Center Ivan Vučetić, the Ruđer Bošković Institute
Funding: HRZZ – COV-HOST-SEQ
Cancer is an exceptionally complex genetic disease and the second leading cause of death worldwide. Its progression is driven by both internal and external processes that contribute to extensive genetic and phenotypic heterogeneity, making it a persistent and evolving challenge in research and treatment. This is particularly true for highly metastatic cancers, such as breast and liver cancers, which are major contributors to cancer-related mortality rates globally.
Routine histopathology is sometimes insufficient to determine the origin of secondary tumors, known as cancers of unknown primary (CUP), which account for 3–5% of all cancers and remain a clinical challenge. We are developing methods to accurately identify the cancer’s cell of origin (COO) by modeling the relationship between the chromatin characteristics of the COO and the cancer’s mutational landscape, determined from whole-genome sequencing (WGS) or whole-exome sequencing (WXS) data. We are investigating how various genomic features influence COO prediction across different cancer types to better understand the oncogenic events driving carcinogenesis.
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Cancer is an exceptionally complex genetic disease and the second leading cause of death worldwide. Its progression is driven by both internal and external processes that contribute to extensive genetic and phenotypic heterogeneity, making it a persistent and evolving challenge in research and treatment. This is particularly true for highly metastatic cancers, such as breast and liver cancers, which are major contributors to cancer-related mortality rates globally.
Routine histopathology is sometimes insufficient to determine the origin of secondary tumors, known as cancers of unknown primary (CUP), which account for 3–5% of all cancers and remain a clinical challenge. We are developing methods to accurately identify the cancer’s cell of origin (COO) by modeling the relationship between the chromatin characteristics of the COO and the cancer’s mutational landscape, determined from whole-genome sequencing (WGS) or whole-exome sequencing (WXS) data. We are investigating how various genomic features influence COO prediction across different cancer types to better understand the oncogenic events driving carcinogenesis.
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Modern lifestyle factors, including sedentary behavior, increased alcohol consumption, and poor dietary habits, have contributed to a rising incidence of various cancers. One of the most concerning trends is the growing prevalence of hepatocellular carcinoma (HCC), particularly linked to metabolic dysfunction-associated steatotic liver disease (MASLD), a condition formerly known as nonalcoholic fatty liver disease (NAFLD). The rising incidence and mortality of HCC underscore the need to understand its molecular pathways to develop targeted therapies. Identifying early diagnostic markers or therapeutic targets could improve detection, treatment, and patient outcomes.
In collaboration with the group led by Prof Ralf Weiskirchen, we investigated the role of the lipid metabolism protein PLIN5 in the pathology of NAFLD and HCC. This study utilized advanced research approaches, including transcriptome, microbiome, and lipidomics analyses, in a murine MAFLD model to uncover new insights into disease mechanisms.
Collaborators: prof. dr. Ralf Weiskirchen, University Hospital RWTH Aache
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To better understand the mechanisms underlying its pathogenesis of HCC, it is crucial to develop reliable models both in vivo and in vitro. While the HepG2 cell line is widely used for HCC research, it does not fully replicate all biological processes and gene expression patterns observed in the actual disease. The aim of this collaboration was to identify a robust set of genes that could be further investigated in patient samples.
Collaborators: Prof. Petra Korać, Faculty of Science, University of Zagreb
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Chemotherapy is often a major driver of cancer evolution, as it applies selective pressure that can lead to the emergence of resistant clones. To effectively eliminate cancer, precision medicine must be applied to target each tumor’s unique characteristics, ensuring that no resistant clones persist to drive further progression. In collaboration with Prof. Inga Urlić, we utilized single-cell RNA sequencing to analyze changes in the cellular population of osteosarcoma patients. Our goal was to identify which cell populations were responsible for recurrence by examining samples taken before, during, and after chemotherapy, as well as during cancer relapse.
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Fundings: Labena 10X challenge
Early life adversity is the strongest environmental risk factor for psychopathology and is associated with increased disorder severity, comorbidity, chronicity and treatment resistance. Determining the altered biology responsible for how early adversity raises risk of psychiatric disorders is key to develop interventions and treatments for a large portion of patients. The overall goal of this project is to identify molecular and cellular mechanisms of psychiatric risk in the insular cortex (insula) – a highly important brain area relevant to psychiatric disorders – to provide a springboard for accurate patient subtyping and personalised drug development. Firstly, we will deeply phenotype the human insula in neurotypical controls using single-cell, spatial transcriptomics and mass spectrometry imaging, and make this atlas freely available to the neuroscience community. We will then study a large sample of individuals with depression, PTSD and controls, with and without early adversity, to identify transcriptomic changes and biological clusters related to exposure and risk in the insular cortex. Lastly, we will validate the features driving the identified biological clusters using our single-cell and spatial omics approaches, providing functional insight into the genes, cell types and pathways affected. This innovative approach will contribute to the identification of new biological subtype-based treatment approaches for psychopathology, to overcome trial-and-error prescribing
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Fundings:
Features of exposure to childhood adversity in the insular cortex in MDD and PTSD (TrauMAP),
ERA-NET Neuron Joint Transnational Call – Resilience and Vulnerablitily in Mental Health
Division of Molecular Biology, Department of Biology, Faculty of Science, University of Zagreb
Horvatovac 102a
10000 Zagreb
Croatia
+38514606276
bioinfo@bioinfo.hr
Group leader and Full Professor of Bioinformatics at the Faculty of Science, University of Zagreb
While studying molecular biology at the University of Zagreb he developed a strong interest in applying computational methods and approaches to biosciences. For his master thesis he worked on a problem in X-ray crystallography and developed a program for absorption correction of scattered X-ray data. He obtained his PhD in Bioinformatics/Biochemistry, still pursuing his structural biology interests, working on a computational prediction of structural and physicochemical properties of DNA. He spent 10 years as a research fellow at the International Center for Genetic Engineering and Biotechnology in Trieste, Italy, where he also worked on computational prediction and classification of protein domains using machine learning approaches.
In 2002 he established a computational biology group at the Zagreb University, where he moved permanently in 2006 with the EMBO Young Investigators Programme installation grant, and directed the scientific interests towards the newly emerging field of genomics. His bioinformatics group develops computational tools and uses machine learning techniques to tackle open questions in developmental genomics and metagenomics.
In 2011 he became full professor at the Faculty of Science at Zagreb University. He had several international appointments, including a 4-year adjunct professorship at the University of Oslo, Norway and a two-year adjunct professorship at the University of Skövde, Sweden. From 2008 to 2012 he served as the head of the Division of Biology, Faculty of Science at University of Zagreb and was responsible for managing a division of ~150 staff.
He is involved in teaching four graduate-level courses: Bioinformatics, Algorithms and programming, Statistics and machine learning and Computational genomics. During his time as a group leader more than 30 doctoral and master students graduated under his supervision. Some of his graduates continued with PhD and postdoctoral training at prestigious universities around the world, including LMB Cambridge, UK; EMBL, Heidelberg, Germany; RIKEN, Japan and ETH, Zurich, Switzerland.
His scientific track-record includes more than 60 publications in high-level journals and talks in many renowned institutions throughout the world. His research topics are: developmental and differentiation genomics, metagenomics, population genomics and glycomics, origins of multicellularity, epigenomics of cancer, development of computational methods and application of machine learning in genomics and molecular biology.
He is the reviewer in a number of scientific journals, as well as national and international funding bodies and programmes, such as ESF Programme, EC FP7, H2020, and Horizon Europe Programmes, Estonian National Funding Agency, Hungarian National Funding Agency, Flanders Research Foundation, The Netherlands ZonMw Vidi Programme, Croatian National Funding Agencies. He reviewed program applications for Croatian pre-accession and accession structural funds.
Prof. Vlahoviček is a Fellow of the Academia Europaea, and a member of several professional societies, at the national and international level. Professor Vlahoviček is a strong proponent of science reforms in Croatia and evidence-based policy making. He served in the steering committee of Croatia’s highly successful science funding body, the Unity through Knowledge Fund (UKF) and has participated in several strategy-drafting panels at the university and national level. He also served as the Member of the Steering Committee of the Ruđer Bošković Institute, a leading Croatian research entity in natural sciences, with ~900 staff.