Centre of Biostatistics and Bioinformatics Analysis

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A new core facility is being established at the Medical University of Gdańsk in the form of Centre of Biostatistics and Bioinformatics Analysis.

The idea of the Centre of Biostatistics and Bioinformatics Analysis is to facilitate the work of research teams by increasing the scientific excellence of the published results. The core facility’s key area of operation is to support the process of scientific research and clinical research in the field of biostatistics and bioinformatics, especially in the context of the Priority Research Areas, implemented under the “Excellence Initiative – Research University” program. The Centre of Biostatistics and Bioinformatics Analysis employs biostatisticians and bioinformatists whose work is aimed at strengthening interdisciplinarity in research conducted at the MUG.

The core facility offers a wide range of services related to the broadly understood biostatistical and bioinformatic analysis as well as big data analysis. The activity profile includes mainly support for projects based on high-throughput DNA and RNA sequencing (including single cell analysis), as well as other scientific initiatives that require processing of large amounts of data. Additionally, the activities of the unit will include the use of artificial intelligence in the processing of imaging data and the classification of patient samples.

This is made possible by an advanced computer infrastructure, which creates space for ground-breaking scientific research based on sophisticated calculations. On the technical level, high-quality biostatistical analysis allows for the extraction of the maximum amount of objective information, which ultimately translates into high-quality research work. In this spirit, the places particular emphasis on the high quality of computational processes, thus increasing the MUG’s project capacity.

The effective conduct of advanced scientific research is possible thanks to a structure that facilitates the comprehensive collection and processing of biostatistical, bioinformatic and clinical imaging data. This structure provides advanced data processing tools that facilitate the proper design of research projects. Thanks to professional statistical and biostatistical analysis, it enables and significantly accelerates their comprehensive implementation.


Overview of the services provided

The Centre of Biostatistics and Bioinformatics Analysis is a scientific unit that provides comprehensive support for researchers in planning, designing, managing and reporting research projects related to clinical, epidemiological and laboratory research.

We would like to inform you that the Medical University of Gdańsk possesses an unlimited single-user license of SPSS software for the Windows operating system. If you are interested in obtaining detailed information, please contact the Centre of Biostatistics and Bioinformatics Analysis.

Cooperation areas:

– grant projects: designing a scientific research and planning biostatistical analyses (analysis of the sample size/ strength of statistical tests, proposal and description of the statistical methodology),

– scientific publications/abstracts: describing the statistical methodology, statistical analysis of the research questions posed, describing and interpreting the results, presenting the results in graphical and tabular form (in accordance with the recommendations of a scientific journal),

– scientific reviews: writing answers to the questions/suggestions of reviewers related to statistical analysis,

– medical data: database design and management, data cleaning, data quality maintenance,

– biostatistics consultations: educating in designing scientific research, giving advice on collecting and managing data, supporting the selection of statistical methods, helping in the interpretation of results and in the process of evaluating the quality of scientific publications.

Detailed description of the services provided

The Centre of Biostatistics and Bioinformatics Analysis provides a wide range of comprehensive services in the field of advanced biostatistical and bioinformatic analysis. The services are offered primarily to scientists conducting clinical, epidemiological, population, molecular and translational research. The computational techniques offered by the Centre are listed below.

Description of the services provided by the Centre of Biostatistics and Bioinformatics Analysis (54.3 KB)

The Centre of Biostatistics and Bioinformatics Analysis offers a free-of-charge hour of consultation in the field of biostatistics, bioinformatics and artificial intelligence applied to medical data. In the need of a complex analysis, the cost of the service will be assessed individually.

Our publications

1. Environmental exposure to persistent organic pollutants measured in breast milk of lactating women from an urban area in central Poland.
Grešner P, Zieliński M, Ligocka D, Polańska K, Wąsowicz W, Gromadzińska J. Environ Sci Pollut Res Int. 2021 Jan;28(4):4549-4557 doi: 10.1007/s11356-020-10767-3

2. Clustered microRNAs: The molecular mechanism supporting the maintenance of luteal function during early pregnancy.
Przygrodzka E, Sokołowska G, Myszczynski K, Krawczynski K, Kaczmarek MM. FASEB J. 2020 May;34(5):6582-6597 doi: 10.1096/fj.201903007RR

3. Rad51 paralogs and the risk of unselected breast cancer: A case-control study.
Grešner P, Jabłońska E, Gromadzińska J. PLoS One. 2020 Jan 6;15(1):e0226976 doi: 10.1371/journal.pone.0226976

4. The Discovery of a LEMD2-Associated Nuclear Envelopathy with Early Progeroid Appearance Suggests Advanced Applications for AI-Driven Facial Phenotyping.
Marbach F, Rustad CF, Riess A, Đukić D, Hsieh TC, Jobani I, Prescott T, Bevot A, Erger F, Houge G, Redfors M, Altmueller J, Stokowy T, Gilissen C, Kubisch C, Scarano E, Mazzanti L, Fiskerstrand T, Krawitz PM, Lessel D, Netzer C. Am J Hum Genet. 2019 Apr 4;104(4):749-757 doi: 10.1016/j.ajhg.2019.02.021

5. Spectrum of Epithelial-Mesenchymal Transition Phenotypes in Circulating Tumour Cells from Early Breast Cancer Patients.
Markiewicz A, Topa J, Nagel A, Skokowski J, Seroczynska B, Stokowy T, Welnicka-Jaskiewicz M, Zaczek AJ. Cancers (Basel). 2019 Jan 9;11(1):59 doi: 10.3390/cancers11010059

6. Comparison of three variant callers for human whole genome sequencing.
Supernat A, Vidarsson OV, Steen VM, Stokowy T. Sci Rep. 2018 Dec 14;8(1):17851 doi: 10.1038/s41598-018-36177-7

7. Sequencing of organellar genomes of Gymnomitrion concinnatum (Jungermanniales) revealed the first exception in the structure and gene order of evolutionary stable liverworts mitogenomes.
Myszczyński K, Górski P, Ślipiko M, Sawicki J. BMC Plant Biol. 2018 Dec 3;18(1):321 doi: 10.1186/s12870-018-1558-0

8. Enhanced detection of circulating tumor DNA by fragment size analysis.
Mouliere F, Chandrananda D, Piskorz AM, Moore EK, Morris J, Ahlborn LB, Mair R, Goranova T, Marass F, Heider K, Wan JCM, Supernat A, Hudecova I, Gounaris I, Ros S, Jimenez-Linan M, Garcia-Corbacho J, Patel K, Østrup O, Murphy S, Eldridge MD, Gale D, Stewart GD, Burge J, Cooper WN, van der Heijden MS, Massie CE, Watts C, Corrie P, Pacey S, Brindle KM, Baird RD, Mau-Sørensen M, Parkinson CA, Smith CG, Brenton JD, Rosenfeld N. Sci Transl Med. 2018 Nov 7;10(466):eaat4921 doi: 10.1126/scitranslmed.aat4921

9. Copy number signatures and mutational processes in ovarian carcinoma.
Macintyre G, Goranova TE, De Silva D, Ennis D, Piskorz AM, Eldridge M, Sie D, Lewsley LA, Hanif A, Wilson C, Dowson S, Glasspool RM, Lockley M, Brockbank E, Montes A, Walther A, Sundar S, Edmondson R, Hall GD, Clamp A, Gourley C, Hall M, Fotopoulou C, Gabra H, Paul J, Supernat A, Millan D, Hoyle A, Bryson G, Nourse C, Mincarelli L, Sanchez LN, Ylstra B, Jimenez-Linan M, Moore L, Hofmann O, Markowetz F, McNeish IA, Brenton JD. Nat Genet. 2018 Sep;50(9):1262-1270 doi: 10.1038/s41588-018-0179-8

10. Plastid super-barcodes as a tool for species discrimination in feather grasses (Poaceae: Stipa).
Krawczyk K, Nobis M, Myszczyński K, Klichowska E, Sawicki J. Sci Rep. 2018 Jan 31;8(1):1924 doi: 10.1038/s41598-018-20399-w

11. Duplicated Enhancer Region Increases Expression of CTSB and Segregates with Keratolytic Winter Erythema in South African and Norwegian Families.
Ngcungcu T, Oti M, Sitek JC, Haukanes BI, Linghu B, Bruccoleri R, Stokowy T, Oakeley EJ, Yang F, Zhu J, Sultan M, Schalkwijk J, van Vlijmen-Willems IMJJ, von der Lippe C, Brunner HG, Ersland KM, Grayson W, Buechmann-Moller S, Sundnes O, Nirmala N, Morgan TM, van Bokhoven H, Steen VM, Hull PR, Szustakowski J, Staedtler F, Zhou H, Fiskerstrand T, Ramsay M. Am J Hum Genet. 2017 May 4;100(5):737-750 doi: 10.1016/j.ajhg.2017.03.012

12. Lipid peroxidation and glutathione peroxidase activity relationship in breast cancer depends on functional polymorphism of GPX1.
Jablonska E, Gromadzinska J, Peplonska B, Fendler W, Reszka E, Krol MB, Wieczorek E, Bukowska A, Gresner P, Galicki M, Zambrano Quispe O, Morawiec Z, Wasowicz W. BMC Cancer. 2015 Oct 7;15:657 doi: 10.1186/s12885-015-1680-4

13. Dysregulation of markers of oxidative stress and DNA damage among nail technicians despite low exposure to volatile organic compounds.
Grešner P, Stepnik M, Król MB, Swiercz R, Smok-Pieniazek A, Twardowska E, Gromadzińska J, Wasowicz W. Scand J Work Environ Health. 2015 Nov;41(6):579-93 doi: 10.5271/sjweh.3523

14. Expression of selenoprotein-coding genes SEPP1, SEP15 and hGPX1 in non-small cell lung cancer.
Gresner P, Gromadzinska J, Jablonska E, Kaczmarski J, Wasowicz W. Lung Cancer. 2009 Jul;65(1):34-40 doi: 10.1016/j.lungcan.2008.10.023

15. imPlatelet classifier: image-converted RNA biomarker profiles enable blood-based cancer diagnostics.
Pastuszak K, Supernat A, Best MG, In ‘t Veld SGJG, Łapińska-Szumczyk S, Łojkowska A, Różański R, Żaczek AJ, Jassem J, Würdinger T, Stokowy T. Mol Oncol. 2021 May 20. doi: 10.1002/1878-0261.13014. Online ahead of print. PMID: 34013585

16. Bortezomib induces methylation changes in neuroblastoma cells that appear to play a significant role in resistance development to this compound.
Łuczkowska K, Sokolowska KE, Taryma-Lesniak O, Pastuszak K, Supernat A, Bybjerg-Grauholm J, Hansen LL, Paczkowska E, Wojdacz TK, Machaliński B. Sci Rep. 2021 May 10;11(1):9846. doi: 10.1038/s41598-021-89128-0. PMID: 33972578

17. Transcriptomic landscape of blood platelets in healthy donors.
Supernat A, Popęda M, Pastuszak K, Best MG, Grešner P, Veld SI’, Siek B, Bednarz-Knoll N, Rondina MT, Stokowy T, Wurdinger T, Jassem J, Żaczek AJ. Sci Rep. 2021 Aug 3;11(1):15679. doi: 10.1038/s41598-021-94003-z. PMID: 34344933

In order to set the date and consultation procedure, please contact us by e-mail at the adress of the Centre of Biostatistics and Bioinformatics Analysis.

The Centre of Biostatistics and Bioinformatics Analysis Events Forum

13.05.2023 – Peter Grešner Ph.D., Elements of Experimental Desig lecutre, delivered as part of the Essentials of a Young Researcher course

10.09.2021 – Kamil Myszczyński, Ph.D. and Krzysztof Pastuszak, M. Eng., lectures as part of the Meet Biotech Online! #4 Bioinformatyka – z czym to się je?

18.04.2021 – Peter Grešner Ph.D., lecutre Kaplan-Meier analysis (...how to understand and interpret it)

14.04.2021 – Open Day 2021 – interview with Anna Supernat, Ph.D. as part of the Science is People project

26.03.2021 – Presentation of the Centre of Biostatistics and Bioinformatics Analysis activities in the context of Artificial intelligence and big data

09.02.2021 – II. R programming and biomedical analytics workshop

16.12.2020 – Inspiring conversations EIT Health of the MUG – Out of the box – Medical innovations

25.11.2020 – R programming workshop



Anna Supernat, Ph.D.
Head of the Centre of Biostatistics and Bioinformatics Analysis
Medical University of Gdańsk
Dębinki 1 Street
80-211 Gdańsk
Phone: 58 349 14 38


Main staff


Anna Supernat, Ph.D. – Head

A graduate of the Intercollegiate Faculty of Biotechnology at the University of Gdańsk and the Medical University of Gdańsk. She completed her doctoral thesis at the Department of Cell Biology of the MUG, under the supervision of Prof. Anna Żaczek. The subject of her interest is the molecular basis of tumours, especially in the field of liquid biopsies analysed by high-throughput sequencing. She has authored 19 publications in peer-reviewed journals, participated in numerous international conferences, is an expert at the National Center for Research and Development (NCBR), and is the manager of grants awarded by the National Science Centre (NCN) and NCBR.


Peter Grešner, Ph.D. – specialist biostatistician

Biophysicist, specialist in biomedical physics and methods of statistical analysis in biomedical research. A graduate of the Faculty of Mathematics, Physics and Computer Science at the Comenius University in Bratislava (Slovakia). In 2006-2020, he was professionally associated with the Department of Toxicology and Carcinogenesis of the J. Nofer Institute of Occupational Medicine in Lodz. Scientific interests include issues related to biochemistry, molecular biology, biostatistics and bioinformatics, mainly in the context of neoplastic processes caused by environmental conditions. Author or co-author of over 20 scientific publications and numerous conference reports. Manager or co-contractor of several scientific projects, including prestigious projects financed by the European Union, NATO Science Program and the National Science Centre (NCN).


Kamil Myszczyński, Ph.D. – specialist bioinformatician

A graduate of the Faculty of Biology and Biotechnology at the University of Warmia and Mazury in Olsztyn. Specialist in analysis of biological data obtained from high-throughput methods. He is interested in the development and implementation of bioinformatic analysis protocols, directions of development of sequencing techniques and the role of individual fractions of nucleic acids in the organism. Co-contractor of over a dozen projects related to genomics and transcriptomics including humans, mammals, plants, bacteria and fungus. Author or co-author of over 20 scientific publications.


Krzysztof Pastuszak, M. Eng. – specialist bioinformatician, Artificial Intelligence specialist

Bioinformatician, passionate about liquid biopsies in oncological diagnosis, especially with the assistance of artificial intelligence. He graduated with honors with degree in Computer Science from Gdańsk University of Technology. Ph.D. student and research assistant at the Department of Algorithms and Systems Modeling at Gdańsk University of Technology. He has been cooperating with Laboratory of Translational Oncology at the Medical University of Gdańsk since 2019. Besides bioinformatics, he is interested in analysis of algorithms and applications of graph theory.


Sebastian Cygert, Ph.D. – Artificial Intelligence consultant

A graduate of the Faculty of Cryptology at Military University of Technology and of the Applied Computer Science at Warsaw University of Technology. The subject of his master’s thesis was the simulation of relativistic heavy ion collisions. Currently he is a PhD student at Gdańsk University of Technology, where he works on the ability to generalize visual perception models and using compression methods for neural networks. He has broad experience in industrial sector (Samsung, Amazon, Moody’s Analitycs). He worked on the Amazon Scout autonomous vehicle project. Author of many publications on parallel computing and machine learning (including image and speech recognition, detection of surgical instruments, methods of uncertainty estimation).


Małgorzata Madej, M.A. – specialist in administrative support for projects

A graduate of the Faculty of Biology at the University of Gdańsk. Passionate about various project management methodologies, she completed post-graduate studies at the Faculty of Organization and Management of the Łódz University of Technology. She has many years of experience in design documentation and administrative work. Work at a research institute and a wide range of knowledge resulted in the development from scratch and implementation of the project management methodology and training of people responsible for maintaining project documentation. In a large international corporation, she developed and implemented a three-way service management platform in a network of points of sale.


Anna Koelmer, M.A. – specialist biostatistician

A graduate of Mathematics at the Gdańsk University of Technology and Computer Science and Econometrics at the University of Gdańsk. She started her employment at the Medical University of Gdańsk by working at the MUG’s Main Library, where she became interested in the issue of open data in medical sciences. Member of the Team for Open Science at the MUG. Currently an employee of the Clinical Research Support Centre. In addition to data analysis, her interests include research methodology and scientific information.

Young staff mentored by the Centre of Biostatistics and Bioinformatics Analysis


Maksym Jopek, Eng. – bioinformatician-trainee

Analyst and software engineer. A graduate of Automation and Robotics at the Faculty of Electrical and Control Engineering at the Gdańsk University of Technology. Passionate about machine learning and data analysis. Member of IAESTE Gdansk and the GRADIENT science club. Currently employed as a bioinformatist-trainee at the Centre of Biostatistics and Bioinformatics Analysis, where he participates in the implementation of projects related to high-throughput sequencing of liquid biopsies taken from oncology patients.


Radosław Mazur – bioinformatician-trainee

Enthusiast of application of machine learning and big data in life sciences. Currently, a trainee in the Centre of Biostatistics and Bioinformatics Analysis. Here, he takes part in research connected with artificial intelligence, liquid biopsies, and oncological targeted therapy response. He is a student of the Intercollegiate Faculty of Biotechnology at the University of Gdańsk and Medical University of Gdańsk.


Michał Sieczczyński, Eng. – student of the Gdańsk University of Technology cooperating with the research team

Student of Computer Science at the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk Tech. Currently a software development intern. Enthusiast of artificial intelligence and machine learning, in particular deep learning. Active member of the GRADIENT scientific association. At the Centre of Biostatistics and Bioinformatics Analysis collaborating on a project related to the analysis of liquid biopsy samples.


Antoni Rutkowski, Eng. – graduate of the Gdańsk University of Technology, cooperating with the research team

A Python programmer by profession, in his free time dealing with issues related to artificial intelligence, machine learning and their use in areas including oncological diagnostics and data analysis. In the ImPlatelet project, he is responsible for the broadly understood preprocessing of data.


Franciszek Górski, Eng. – graduate of the Gdańsk University of Technology, cooperating with the research team

A graduate of Computer Science at the Faculty of Electronics, Telecommunications, and Informatics, currently continuing this course on a Master’s degree. He is passionate about deep and machine learning, a member of the board of the GRADIENT scientific association of Gdańsk Tech gathering students who want to develop their interests in the field of deep learning. His professional interests lie in the application of machines and deep learning in medicine, especially in medical imaging. He gained his professional experience working in R&D projects as a programmer, implementing machine learning models, including deep learning. At the Centre of Biostatistics and Bioinformatics Analysis, he collaborates on the development of a cancer classifier on liquid biopsy data.


Piotr Juszczyk, Eng. – graduate of the Gdańsk University of Technology, cooperating with the research team

p<>. A graduate of Data Engineering at the Faculty of Electronics, Telecommunications and Informatics and a student of Computer Science at the second degree studies. A software engineer by profession working in numerous technologies, incl. C, C ++, and Python. Enthusiast of machine learning, data analysis and good programming practices. He works with the team to help process data and develop a cancer classifier from liquid biopsy data based on decision trees.


Sebastian Lewalski, Eng. – student of the Gdańsk University of Technology cooperating with the research team

A graduate of Automation and Robotics at the Faculty of Electrical and Control Engineering at the Gdańsk University of Technology and a student Computer Science at the Master’s degree studies. On a daily basis he deals with the development of embedded systems, including IoT solutions based on the use of machine learning. An enthusiast of artificial intelligence methods and research on new algorithms for learning systems. He is collaborating with the team on a classifier project based on the use of liquid biopsy sample analysis.