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.
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 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.
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.
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.
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)
Big Data analysis pipelines for large sets of SARS-CoV-2 sequencing data and deep learning methods for predicting severity
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.
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
We provide informatics support for groups in the FIEK Biotechnology consortium where the aim is the development of new molecular biomarkers
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
For an extensive list of all published works, click on the button below.
N Solymosi, AG Tóth, SÁ Nagy, I Csabai, C Feczkó, T Reibling, T Németh
PeerJ 13, e18802 (2025)
O Kilim, A Olar, A Biricz, L Madaras, P Pollner, Z Szállási, Z Sztupinszki, I Csabai
npj Precis. Onc. 9, 27 (2025)
N Deutsch, Z Dosztányi, I Csabai et al.
Bioinformatics 40, 11 (2024)
M Diossy, V Tisza, H Li et al.
npj Precis. Onc. 8, 208 (2024)
Á Becsei, A Fuschi, S Otani et al.
Nat Commun 15, 7551 (2024)
O Kilim, J Báskay, A Biricz, Z Bedőházi, P Pollner, I Csabai
Bioinspir. Biomim. 19 056016 (2024)
RN Fiam, C István, S Norbert
Briefings in Bioinformatics 25, 4 (2024)
A Prosz, P Sahgal, BM Huffman et al.
npj Precis. Onc. 8, 87 (2024)
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.
Pázmány Péter sétány 1/A., Budapest, H-1117, Hungary
csabai@elte.hu
istvan.csabai@ttk.elte.hu
+361 372 2826
+361 372 2500/6576