Research Group

Our group's focus is data-intensive biology-related research with particular emphasis on collaborative reproducible data analysis and cutting-edge machine-learning techniques

Our goals and methods

Most of our research topics are highly interdisciplinary and require a wide range of expertise. To this end both the scientific backgrounds of our team members and our analysis approaches are diverse and versatile.

Our background

Our group combines the expertise of physicists, biologists, bioinfomaticians and biotechnologists.


For an even wider perspective, we routinely collaborate with microbiologists, virologists, immunologists, medical doctors and veterinary doctors.

Big data analysis

Many of our projects require the analysis of large data sets (e.g. NGS raw data, methylation, etc.). We are experienced in the computational exploration and visualization of such data sets and are also continously developing new methods for these purposes.

Artificial intelligence

Keeping up with worldwide scientific innovations, our team is well-versed in various machine-learning techniques and has built high-performing neural networks for specific tasks.

Research projects

Europe Horizon - projects on infectious diseases

Europe Horizon - projects on infectious diseases

These projects aim to generate and distribute high-quality actionable information for evidence-based early warning, risk assessment and monitoring of emerging infectious diseases (EIDs) and antimicrobial resistance (AMR)

SARS-CoV-2 research

SARS-CoV-2 research

Big Data analysis pipelines for large sets of SARS-CoV-2 sequencing data and deep learning methods for predicting severity

Collaborative analysis platforms (Kooplex)

Collaborative analysis platforms (Kooplex)

Kooplex is an open source tool for data exploration and visualization with many collaborative features. It is a platform to analyze data, develop algorithms, workflows and/or create reports with digested data in interactive formats.

Deep learning and image analysis

Deep learning and image analysis

We develop deep learning algorithms for accurate and high-performing (image) classification tasks in a variety of fields.



We build models for the accurate prediction of chronological age based on biological parameters, in most cases DNA-methylation values

Biomarker development (FIEK)

Biomarker development (FIEK)

We provide informatics support for groups in the FIEK Biotechnology consortium where the aim is the development of new molecular biomarkers

Hungarian Oncogenome

Hungarian Oncogenome

We provide bioinformatics assistence and support for the "Hungarian Oncogenome and Personalised Tumor Diagnostics and Therapy National project" with the goal of creating a detailed molecular genetic characterization of the most common tumors in Hungary


István Csabai, DSc

Professor, Head of Research Group csabai@elte.hu

Gergely Palla, DSc

Professor palla.gergely@ttk.elte.hu

Krisztián Papp, PhD

Senior Research Fellow krisztian.papp@ttk.elte.hu

Péter Pollner, PhD

Senior Research Fellow peter.pollner@ttk.elte.hu

József Stéger, PhD

Research Fellow jozsef.steger@ttk.elte.hu

Dávid Visontai, PhD

Research Fellow david.visontai@ttk.elte.hu

Anna Medgyes-Horváth, PhD

Research Fellow horvath.anna@ttk.elte.hu

Anikó Mentes, PhD

Research Fellow aniko.mentes@ttk.elte.hu

Orsolya Pipek, PhD

Research Fellow orsolya.pipek@ttk.elte.hu

Norbert Solymosi, PhD

University of Veterinary Medicine solymosi@staff.elte.hu

Sándor Spisák, PhD

HUN-REN, Epigenetic and Genome Editing Research Group spisak.sandor@ttk.hu

Ákos Gellért, PhD

HUN-REN, ÁTKI gellert.akos@vmri.hun-ren.hu

Anna Apari, MSc

Assistant Research Fellow aparianna5@gmail.com

Ágnes Becsei, MSc

PhD student agnes.becsei@ttk.elte.hu

Alex Olar, MSc

PhD student olar.alex@ttk.elte.hu

András Biricz, MSc

PhD student andras.biricz@ttk.elte.hu

Adrienn Tóth, MSc

PhD student, University of Veterinary Medicine tothadrienngreta@gmail.com

Zsolt Bedőházi, MSc

PhD student zsoltbedohazi@inf.elte.hu

Oz Kilim, MSc

PhD student ozkilim@student.elte.hu

Csaba Kiss, MSc

PhD student

Mirkó Mocskonyi, MSc

PhD student mocskonyi.mirko@gmail.com

Balázs Pál, MSc

PhD student pal.balazs@ttk.elte.hu

Regina Fiam, BSc

MSc student fregin@student.elte.hu

Past Members

Zoltán Udvarnoki

PhD student

Dezső Ribli

PhD student

Bálint Ármin Pataki

PhD student

Judit Börcsök

PhD student

András Major

BSc student

János Szalai-Gindl

Assistant Lecturer


Department of Immunology

ELTE TTK, Budapest, Hungary


Budapest, Hungary

Danish Cancer Society

Coppenhagen, Denmark

Boston Children's Hospital

Harvard Medical School, Boston, USA

Institute of Molecular Life Sciences

HUN-REN TTK, Budapest, Hungary

Semmelweis University

Various departments, Budapest, Hungary

Recent publications

For an extensive list of all published works, click on the button below.

Annotated dataset for training deep learning models to detect astrocytes in human brain tissue

A Olar, T Tyler, P Hoppa, E Frank, I Csabai, I Adorjan, P Pollner
Scientific Data 11 (1), 96 (2024)

Biologically informed deep learning for explainable epigenetic clocks

A Prosz, O Pipek, J Börcsök, G Palla, Z Szallasi, S Spisak, I Csabai
Scientific Reports 14 (1), 1306 (2024)

Systematic detection of co-infection and intra-host recombination in more than 2 million global SARS-CoV-2 samples

OA Pipek, A Medgyes-Horváth, J Stéger et al.
Nature Communications 15 (1), 517 (2024)

The potential of Hungarian bauxite residue isolates for biotechnological applications

V Feigl, A Medgyes-Horváth, A Kari et al.
Biotechnology Reports 41, e00825 (2023)

Bacterial colony size growth estimation by deep learning

SÁ Nagy, L Makrai, I Csabai, D Tőzsér, G Szita, N Solymosi
BMC microbiology 23 (1), 307 (2023)

Genomic Landscape of Normal and Breast Cancer Tissues in a Hungarian Pilot Cohort

O Pipek, D Alpár, O Rusz et al.
International Journal of Molecular Sciences 24 (10), 8553 (2023)


The office of István Csabai, the head of our research group is located on the 5th floor of the building at Pázmány Péter sétány 1/A, with office number 5.102.

Our Address

Pázmány Péter sétány 1/A., Budapest, H-1117, Hungary

Email Us


Call Us

+361 372 2826
+361 372 2500/6576