We cordially invite you to take advantage of complimentary consultations and analyses at the CABiB.
The Center for Biostatistical and Bioinformatics Analysis (CABiB) offers researchers at Gdańsk Medical University free biostatistical, bioinformatical, and artificial intelligence support. Engage with our experts through consultations or request a tailored analysis at no cost, provided within a limit of up to 50 specialist hours.
Why participate?
- Receive professional advice and substantive support.
- Benefit from a personalized approach tailored to your research requirements.
- Utilize custom analyses designed specifically for your project.
- CABiB is dedicated to enhancing scientific endeavors through cutting-edge technologies. Join us and leverage our expertise!
Consultation form for Centre of Biostatistics and Bioinformatics Analysis
CENTRE OF BIOSTATISTICS AND BIOINFORMATICS ANALYSIS – WHO WE ARE
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.
RANGE OF SERVICES
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.
The Centre of Biostatistics and Bioinformatics Analysis also holds the right to use the GraphPad Prism programme and makes it available to the research staff and employees of the Medical University of Gdańsk. This software not only facilitates advanced analyses but also allows results to be presented clearly and professionally, which is crucial when publishing research results. For installation instructions and a license key, please contact us at our email address centrum.obliczeniowe@gumed.edu.pl. The number of available licenses is limited.
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. Elevated expression of complement factor I in lung cancer cells associates with shorter survival- Potentially via non-canonical mechanism
Felberg A, Bieńkowski M, Stokowy T, Myszczyński K, Polakiewicz Z, Kitowska K, Sądej R, Mohlin F, Kuźniewska A, Kowalska D, Stasiłojć G, Jongerius I, Spaapen R, Mesa-Guzman M, Montuenga LM, Blom AM, Pio R, Okrój M. Transl Res. 2024 Jul;269:1-13. doi: 10.1016/j.trsl.2024.02.003. Epub 2024 Feb 22. PMID: 38395390
2. Immune escape of B-cell lymphoblastic leukemic cells through a lineage switch to acute myeloid leukemia
Bełdzińska-Gądek, K., Zarzycka, E., Pastuszak, K., Borman, K., Lewandowski, K., Zaucha, J. M., & Prejzner, W. Leukemia & Lymphoma, (2024), 1–11. doi.org/10.1080/10428194.2024.2351194. Epub ahead of print. PMID: 38775354
3. Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
Pastuszak K, Sieczczyński M, Dzięgielewska M, Wolniak R, Drewnowska A, Korpal M, Zembrzuska L, Supernat A, Żaczek AJ. Sci Rep. 2024 May 14;14(1):11057. doi: 10.1038/s41598-024-61378-8. PMID: 38744942; PMCID: PMC11094170
4. Dissection of an impact of VDR and RXRA on the genomic activity of 1,25(OH)2D3 in A431 squamous cell carcinoma
Olszewska AM, Nowak JI, Myszczynski K, Słominski A, Żmijewski MA. Mol Cell Endocrinol. 2024 Mar 1;582:112124. doi: 10.1016/j.mce.2023.112124. Epub 2023 Dec 19. PMID: 38123121; PMCID: PMC10872374
5. Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
Jopek MA, Pastuszak K, Cygiert S, Best MG, Wurdinger T, Jassem J, Żaczek AJ, Supernat A. IEEE Journal of Translational Engineering in Health and Medicine, vol. 12, pp. 306-313, 2024, Jan; doi: 10.1109/JTEHM.2024.3360865.
6. PDIA3 modulates genomic response to 1,25-dihydroxyvitamin D3 in squamous cell carcinoma of the skin
Nowak JI, Olszewska AM, Piotrowska A, Myszczyński K, Domżalski P, Żmijewski MA. Steroids. 2023 Nov;199:109288. doi: 10.1016/j.steroids.2023.109288. Epub 2023 Aug 5. PMID: 37549780
7. Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single- spheroid cultures
Giczewska A, Pastuszak K, Houweling M, Abdul KU, Faaij N, Wedekind L, Noske D, Wurdinger T, Supernat A, Westerman BA. Neurooncol Adv. 2023 Nov 5;5(1):vdad134. doi: 10.1093/noajnl/vdad134. PMID: 38047207; PMCID: PMC10691443
8. Metabolomics Meets Clinics: A Multivariate Analysis of Plasma and Urine Metabolic Signatures in Pulmonary Arterial Hypertension
Wawrzyniak R, Grešner P, Lewicka E, Macioszek S, Furga A, Zieba B, J Markuszewski M, Da Browska-Kugacka A. J Proteome Res. 2023 Oct 12. doi: 10.1021/acs.jproteome.3c00255. Epub ahead of print. PMID: 37827514
9. Long-term mortality after transcatheter aortic valve implantation for aortic stenosis in immunosuppression-treated patients: a propensity-matched multicentre retrospective registry-based analysis
Walczewski M, Gąsecka A, Witkowski A, Dabrowski M, Huczek Z, Wilimski R, Ochała A, Parma R, Rymuza B, Grygier M, Jemielity M, Olasińska-Wiśniewska A, Jagielak D, Targoński R, Pastuszak K, Grešner P, Grabowski M, Kochman J. Postepy Kardiol Interwencyjnej. 2023 Sep;19(3):251-256. doi: 10.5114/aic.2023.131478. Epub 2023 Sep 27. PMID: 37854972; PMCID: PMC10580841
10. Platelet RNA enables accurate detection of ovarian cancer: an intercontinental, biomarker identification study
Gao Y, Liu CJ, Li HY, Xiong XM, Li GL, In ‘t Veld SGJG, Cai GY, Xie GY, Zeng SQ, Wu Y, Chi JH, Liu JH, Zhang Q, Jiao XF, Shi LL, Lu WR, Lv WG, Yang XS, Piek JMJ, de Kroon CD, Lok CAR, Supernat A, Łapińska-Szumczyk S, Łojkowska A, Żaczek AJ, Jassem J, Tannous BA, Sol N, Post E, Best MG, Kong BH, Xie X, Ma D, Wurdinger T, Guo AY, Gao QL. Protein Cell. 2023 Jun 7;14(6):579-590. doi: 10.1093/procel/pwac056. PMID: 36905391; PMCID: PMC10246718.
11. Screening of predicted synergistic multi-target therapies in glioblastoma identifies new treatment strategies
Houweling M, Giczewska A, Abdul K, Nieuwenhuis N, Küçükosmanoglu A, Pastuszak K, Buijsman RC, Wesseling P, Wedekind L, Noske D, Supernat A, Bailey D, Watts C,
Wurdinger T, Westerman BA. Neurooncol Adv. 2023 Jun 13;5(1):vdad073. doi: 10.1093/noajnl/vdad073. PMID: 37455945; PMCID: PMC10347974.
12. Tamoxifen decreases ovarian toxicity without compromising cancer treatment in a rat model of mammary cancer
Nynca A, Swigonska S, Ruszkowska M, Sadowska A, Orlowska K, Molcan T, Myszczynski K, Otrocka-Domagala I, Paździor-Czapula K, Kurowicka B, Petroff BK, Ciereszko RE. BMC Genomics. 2023 Jun 13;24(1):325. doi: 10.1186/s12864-023-09423-0. PMID: 37312040; PMCID: PMC10265842
13. Platelet-Based Liquid Biopsies through the Lens of Machine Learning
Cygert S, Pastuszak K, Górski F, Sieczczyński M, Juszczyk P, Rutkowski A, Lewalski S, Różański R, Jopek MA, Jassem J, Czyżewski A, Wurdinger T, Best MG, Żaczek AJ, Supernat A. Cancers (Basel). 2023 Apr 17;15(8):2336. doi: 10.3390/cancers15082336. PMID: 37190262; PMCID: PMC10136732
14. Plasma Proteomics Unveil Novel Immune Signatures and Biomarkers upon SARS-CoV-2 Infection
Urbiola-Salvador V, Lima de Souza S, Grešner P, Qureshi T, Chen Z. Int J Mol Sci. 2023 Mar 27;24(7):6276. doi: 10.3390/ijms24076276. PMID: 37047248; PMCID: PMC10093853
15. Efficacy of intralesional bleomycin in treatment resistant viral warts
Sławińska, Martyna, Jakub Żółkiewicz, Krzysztof Pastuszak, Klaudia Zawadzka, Monika Sikorska, Roman J Nowicki, and Michał Sobjanek. Dermatol Rev/Przegl Dermatol 2022, 109 (4): 272-290. doi:10.5114/dr.2022.123983
16. Super-Mitobarcoding in Plant Species Identification? It Can Work! The Case of Leafy Liverworts Belonging to the Genus Calypogeia
Ślipiko M, Myszczyński K, Buczkowska K, Bączkiewicz A, Sawicki J. Int J Mol Sci. 2022 Dec 8;23(24):15570. doi: 10.3390/ijms232415570. PMID: 36555212; PMCID: PMC9779425
17. Pathway-level mutation analysis in primary high-grade serous ovarian cancer and matched brain metastases
Duchnowska R, Supernat AM, Pęksa R, Łukasiewicz M, Stokowy T, Ronen R, Dutkowski J, Umińska M, Iżycka-Świeszewska E, Kowalczyk A, Och W, Rucińska M, Olszewski WP, Mandat T, Jarosz B, Bieńkowski M, Biernat W, Jassem J. Sci Rep. 2022 Nov 29;12(1):20537. doi: 10.1038/s41598-022-23788-4. PMID: 36446793; PMCID: PMC9708673.
18. Insights into adaptive evolution of plastomes in Stipa L.
Krawczyk K, Myszczyński K, Nobis M, Sawicki J. BMC Plant Biol. 2022 Nov 14;22(1):525. doi: 10.1186/s12870-022-03923-z. PMID: 36372890; PMCID: PMC9661759
19. Detection and localization of early- and late-stage cancers using platelet RNA
In ‘t Veld SGJG, Arkani M, Post E, Antunes-Ferreira M, D’Ambrosi S, Vessies DCL, Vermunt L, Vancura A, Muller M, Niemeijer AN, Tannous J, Meijer LL, Le Large TYS, Mantini G, Wondergem NE, Heinhuis KM, van Wilpe S, Smits AJ, Drees EEE, Roos E, Leurs CE, Tjon Kon Fat LA, van der Lelij EJ, Dwarshuis G, Kamphuis MJ, Visser LE, Harting R, Gregory A, Schweiger MW, Wedekind LE, Ramaker J, Zwaan
K, Verschueren H, Bahce I, de Langen AJ, Smit EF, van den Heuvel MM, Hartemink KJ, Kuijpers MJE, Oude Egbrink MGA, Griffioen AW, Rossel R, Hiltermann TJN, Lee- Lewandrowski E, Lewandrowski KB, De Witt Hamer PC, Kouwenhoven M, Reijneveld JC, Leenders WPJ, Hoeben A, Verdonck-de Leeuw IM, Leemans CR, Baatenburg de Jong RJ, Terhaard CHJ, Takes RP, Langendijk JA, de Jager SC, Kraaijeveld AO, Pasterkamp G, Smits M, Schalken JA, Łapińska-Szumczyk S, Łojkowska A, Żaczek AJ, Lokhorst H, van de Donk NWCJ, Nijhof I, Prins HJ, Zijlstra JM, Idema S, Baayen JC, Teunissen CE, Killestein J, Besselink MG, Brammen L, Bachleitner-Hofmann T, Mateen F, Plukker JTM, Heger M, de Mast Q, Lisman T, Pegtel DM, Bogaard HJ, Jassem J, Supernat A, Mehra N, Gerritsen W, de Kroon CD, Lok CAR, Piek JMJ, Steeghs N, van Houdt WJ, Brakenhoff RH, Sonke GS, Verheul HM, Giovannetti E,
Kazemier G, Sabrkhany S, Schuuring E, Sistermans EA, Wolthuis R, Meijers- Heijboer H, Dorsman J, Oudejans C, Ylstra B, Westerman BA, van den Broek D, Koppers-Lalic D, Wesseling P, Nilsson RJA, Vandertop WP, Noske DP, Tannous BA, Sol N, Best MG, Wurdinger T. Cancer Cell. 2022 Sep 12;40(9):999-1009.e6. doi: 10.1016/j.ccell.2022.08.006. Epub 2022 Sep 1. PMID: 36055228
20. Significance of Dermoscopy in Association with Clinical Features in Differentiation of Basal Cell Carcinoma and Benign Trichoblastic Tumours
Sławińska M, Płaszczyńska A, Lakomy J, Pastuszak K, Biernat W, Sikorska M, Nowicki RJ, Sobjanek M. Cancers (Basel). 2022 Aug 17;14(16):3964. doi: 10.3390/cancers14163964. PMID: 36010957; PMCID: PMC9406107
21. Breaking the limits – multichromosomal structure of an early eudicot Pulsatilla patens mitogenome reveals extensive RNA-editing, longest repeats and chloroplast derived regions among sequenced land plant mitogenomes
Szandar K, Krawczyk K, Myszczyński K, Ślipiko M, Sawicki J, Szczecińska M. BMC Plant Biol. 2022 Mar 9;22(1):109. doi: 10.1186/s12870-022-03492-1. PMID: 35264098; PMCID: PMC8905907
22. Breast cancer circulating tumor cells with mesenchymal features-an unreachable target?
Topa J, Grešner P, Żaczek AJ, Markiewicz A. Cell Mol Life Sci. 2022 Jan 20;79(2):81. doi: 10.1007/s00018-021-04064-6. PMID: 35048186; PMCID: PMC8770434
23. Diagnostic Accuracy of Liquid Biopsy in Endometrial Cancer
Łukasiewicz M, Pastuszak K, Łapińska-Szumczyk S, Różański R, Veld SGJGI’, Bieńkowski M, Stokowy T, Ratajska M, Best MG, Würdinger T, Żaczek AJ, Supernat A, Jassem J. Cancers (Basel). 2021 Nov 16;13(22):5731. doi: 10.3390/cancers13225731. PMID: 34830891;
PMCID: PMC8616122
24. 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 Oct;15(10):2688-2701. doi: 10.1002/1878-0261.13014. Epub 2021 Jun 20. PMID: 34013585; PMCID: PMC8486571
25. Modelling of dark fermentation of glucose and sour cabbage
Sołowski G, Pastuszak K. Heliyon. 2021 Jul 31;7(8):e07690. doi: 10.1016/j.heliyon.2021.e07690. PMID: 34401576; PMCID: PMC8350504
26. 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; PMCID: PMC8333095
27. 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; PMCID: PMC8110815
28. 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
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
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
Recommended
Photo Paweł Sudara/MUG
Contact
Anna Supernat, Dr. Habil.
Head of the Centre of Biostatistics and Bioinformatics Analysis
Medical University of Gdańsk
Dębinki 1 Street
80-211 Gdańsk
Phone: 58 349 90 46
centrum.obliczeniowe@gumed.edu.pl
TEAM
Main staff
Anna Supernat, Dr. Habil. – 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.
Petra Małgorzata Grešner, Ph.D. – senior specialist, 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). Her scientific interests include issues related to biochemistry, molecular biology, biostatistics and machine learning, mainly in the context of neoplastic processes caused by environmental conditions. Author of more than 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. – senior specialist, 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.
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. 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, M. Eng. – junior data analyst
Graduate in Biomedical Engineering at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology. Analyst and software engineer. Currently a doctoral student at the Intercollegiate Faculty of Biotechnology UG & MUG in the Division of Translational Oncology, where he participates in projects related to high-throughput sequencing of liquid biopsies taken from oncology patients. He is passionate about machine learning and athletics. In his spare time, he is involved in consulting medical research projects at the Centre of Biostatistics and Bioinformatics Analysis, providing substantive support.
Michał Sieczczyński, M. Eng. – junior specialist in AI
Graduated with honours with a specialisation in Machine Learning from the Faculty of Computer Science at the Gdańsk University of Technology. At the Centre of Biostatistics and Bioinformatics Analysis, he is involved in the analysis of single-cell sequencing and platelet sequencing data in particular using AI. In addition to bioinformatics and machine learning, he is also interested in quantum computing.