Dr inż. Michał Marczyk, Adiunkt, pokój: 535
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Nota biograficzna:

•10.2014 – obecnie – adiunkt, Zakład Analizy Eksploracyjnej Danych, Wydział Automatyki, Elektroniki i Informatyki, Politechnika Śląska w Gliwicach

•10.2013 – 09.2014 – asystent z doktoratem, Zakład Analizy Eksploracyjnej Danych, Wydział Automatyki, Elektroniki i Informatyki, Politechnika Śląska w Gliwicach

•09.2013 – Rozprawa doktorska z wyróżnieniem: „Przetwarzanie i klasyfikacja danych uzyskiwanych z użyciem wysokoprzepustowych technik pomiarowych biologii molekularnej”

•2012 – 2013 – Politechnika Śląska w Gliwicach, Wydział Automatyki, Elektroniki i Informatyki: Biocybernetyka i Inżynieria Biomedyczna – stacjonarne studia doktoranckie

•2008 – 2013 – Politechnika Śląska w Gliwicach, Wydział Automatyki, Elektroniki i Informatyki: Automatyka i Robotyka – stacjonarne studia doktoranckie

Rozwiń/Zwiń

Zainteresowania naukowe:

•Bioinformatyka, biostatystyka, eksploracyjna analiza danych, uczenie maszynowe

•Analiza oligonukleotydowych mikromacierzy DNA

•Przetwarzanie i modelowanie widm masowych typu MALDI-ToF, LC-MS i IMS

•Analiza danych qRT-PCR

•Przetwarzanie i modelowanie map peptydowych z dwuwymiarowej elektroforezy żelowej

Lista publikacji:

1. Zyla J., Marczyk M., Polanska J.: Reproducibility of Finding Enriched Gene Sets in Biological Data Analysis. In: Fdez-Riverola F., Mohamad M., Rocha M., De Paz J., Pinto T. (eds) 11th International Conference on Practical Applications of Computational Biology & Bioinformatics. PACBB 2017. Advances in Intelligent Systems and Computing, vol 616. p. 146-154 (2017) Springer, Cham ISBN:978-3-319-60815-0

2. Skrzypski MT, Szymanowska-Narloch A, Jassem E, Marczyk M, Polanska J, Biernat W, Rzyman W, Maciejewska A, Pawlowski R, Jassem J: Prognostic value of NK and T-lymphocytes markers in operable non-small cell lung cancer (NSCLC). Journal of Clinical Oncology 2017, 35(15_suppl), p. 11556. ASCO Annual Meeting, Chicago, USA, June 2-6, 2017

3. Skrzypski MT, Marczyk M, Szymanowska A, Kowalczyk A, Maciejewska A, Pawlowski R, Biernat W, Polanska J, Jassem J: Prognostic value of the expression of NKG2D and CD96 in early stage non-small cell lung cancer (NSCLC). Cancer Research 2017, 77(13 Suppl), p. 3700. American Association for Cancer Research Annual Meeting, Washington, USA, April 1-5, 2017

4. Marczyk M, Polanski A, Polanska J: Improving Peak Detection by Gaussian Mixture Modeling of Mass Spectral Signal. In ISBN: 978-1-5386-1037-4, pp. 39-43, 3rd International Conference on Frontiers of Signal Processing ICFSP 2017, Paris, France, September 6-8, 2017

5. Skrzypski MT, Szymanowska-Narloch A, Kowalczyk A, Maciejewska A, Marczyk M, Polanska J, Biernat W, Rzyman W, Jassem J: Prognostic value of NK and T-lymphocytes markers in operable non-small cell lung cancer (NSCLC). Annals of Oncology 2017, 28(supp. 5), p. 1713P. 42nd European Society for Medical-Oncology Congress (ESMO), Madrid, Spain, September 8-12, 2017

6. Zyla J, Marczyk M, Polanska J: Sensitivity, Specificity and Prioritization of Gene Set Analysis When Applying Different Ranking Metrics. In 10th International Conference on Practical Applications of Computational Biology & Bioinformatics, PACBB'16, 1-3 June 2016, Sevilla, Spain. Advances in Intelligent Systems and Computing, vol. 477, p.61-69, Eds. M. Saberi Mohamad, P.M. Rocha, F. Fdez-Riverola, J.F. Domínguez Mayo, F.J. De Paz, Springer International Publishing 2016, ISBN: 978-3-319-40125-6

7. Marczyk M: Improved Detection of 2D Gel Electrophoresis Spots by Using Gaussian Mixture Model. In Bioinformatics Research and Applications, A. Bourgeois, P. Skums, X. Wan and A. Zelikovsky, Editors. Springer International Publishing 2016. p. 284-94, ISBN: 978-3-319-38781-9

8. Skrzypski MT, Marczyk M, Bobowicz M, Czapiewski P, Maciejewska A, Pawlowski R, Polanska J, Jassem J: MicroRNA (MiRNA) expression profiles in early colon cancer (CC) and lung adenocarcinoma (AC). Journal of Clinical Oncology 2015, vol. 33 (suppl; abstr e22062). ASCO Annual Meeting, Chicago, USA, May 29-June 2, 2015

9. Marczyk M, Drazek G, Pietrowska M, Widlak P, Polanska J, Polanski A: Modeling of Imaging Mass Spectrometry Data and Testing by Permutation for Biomarkers Discovery in Tissues. Procedia Computer Science 2015, 51, p. 693-702. International Conference On Computational Science, ICCS 2015, Reykjavík, Iceland, June 1-3, 2015

10. Widlak P, Pietrowska M, Polanska J, Marczyk M, Dziadziuszko R, Rzyman W: Components of Serum Peptidome Can Differentiate between Healthy Controls and Patients with Early Stage Lung Cancer. 16th World Conference on Lung Cancer, 6-9 September 2015, Denver, Colorado, USA. Journal of Thoracic Oncology, 10(9):Suppl.2:S491 ( P1.06-012)

11. Lesniewski-Kmak Krzysztof, Marjanski Tomasz, Zurek Wojciech, Marczyk Michal, Polanska Joanna, Rzyman Witold: Analysis of Factors That Have Impact on Adjuvant Chemotherapy Application in Operated Stage IIA-IV Non-Small Cell Lung Cancer. 16th World Conference on Lung Cancer, 6-9 September 2015, Denver, Colorado, USA. Journal of Thoracic Oncology, 10(9):Suppl.2:S678 (P3.02-033)

12. Binczyk F, Marczyk M and Polanska J: Mixture model based efficient method for magnetic resonance spectra quantification. Bioinformatics and Biomedical Engineering, Lecture Notes in Computer Science, vol. 9044, pp.406-417, ISBN 978-3-319-16480-9, Eds. Ortuño, Francisco, Rojas, Ignacio, 3rd International Work-Conference on Bioinformatics and Biomedical Engineering IWBBIO 2015, Granada, Spain, 15-17.04.2015

13. Marczyk M, Polanska J, Polanski A: Comparison of Algorithms for Profile-Based Alignment of Low Resolution MALDI-ToF Spectra. In Advances in Intelligent Systems and Computing, Vol. 242 of Man-Machine Interactions 3, Gruca A, Czachorski T, Kozielski S, editors. Springer Berlin Heidelberg 2014, p. 193-201 (ISBN: 978-3-319-02308-3), ICMMI 2013, 22-25.10.2013 Brenna, Poland

14. Marczyk M, Polanska J: Methods for quality control of low-resolution MALDI-ToF spectra, Proceedings of 5th International Conference on Bioinformatics Models, Methods and Algorithms p.172-177, ISBN:978-989-758-012-3. BIOSTEC/Bioinformatics 2014, 03-07.03.2014 Angers, FRANCE

15. Foszner P, Gruca A, Polanski A, Marczyk M, Jaksik R, Polanska J: An efficient algorithm for microarray probes re-annotation – the extended version, Transactions on Computational Intelligence XIII, Lecture Notes in Computer Science, Eds. Nguyen NT, Le-Thi HA, vol. 8342:201-218, doi: 10.1007/978-3-642-54455-2_9, 2014, ISBN: 978-3-642-54454-5

16. Marczyk M, Krol L, Polanska J: Automatic detection of outlying microarrays using multi-array quality metrics. Proceedings of International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2014). vol.1 p.738-746, ISBN:978-84-15814-84-9, 7-9.04.2014, Granada, SPAIN

17. Deperas-Kaminska M, Bajinskis A, Marczyk M, Polanska J, Wersall P, Lidbrink E, Ainsbury EA, Guipaud O, Benderitter M, Haghdoost S, Wojcik A: Radiation induced changes in levels of selected proteins in peripheral blood serum of breast cancer patients as a potential triage biodosimeter for large scale radiological emergencies. 41st Annual Meeting of the European Radiation Research Society, ERR2014, September 14-19, 2014, Rhodes, Greece

18. Foszner P. Gruca A. Polanski A. Marczyk M. Jaksik R. Polanska J: Efficient algorithm for microarray probes re-annotation. 3rd International Conference on Computational Collective Intelligence Technologies and Applications ICCCI 2011, Special Session on Computational Collective Intelligence in Bioinformatics, CCIB 2011. 21-23 September 2011, Gdynia, Poland, published in Lecture Notes in Computer Science. Eds. Jedrzejowicz P, Nguyen NT, Hoang K, vol. 6923/2011: 281-289

19. Marczyk M. Jaksik R. Polanski A. Polanska J: Affymetrix Chip Definition Files construction based on custom probe set annotation database. In Eds. R.Katarzyniak, TF.Chiu, CF.Hong, NT.Nguyen, Wydawnictwo Springer Verlag 2011, seria Studies in Computational Intelligence, vol. 381, 2011 “Semantic Methods for Knowledge Management and Communication” , p.135-144. 3rd International Conference on Computational Collective Intelligence Technologies and Applications ICCCI 2011

20. Widlak P. Pietrowska M. Rutkowski T. Wygoda A. Skladowski K. Wojtkiewicz K. Marczyk M. Polanska J: Radiation-related Changes in Serum Proteome Profiles Detected by Mass Spectrometry in Blood of Patients Treated with Radiotherapy Due to Larynx Cancer. International Journal of Radiation Oncology & Biology & Physics 2011, 81(2):S161-162. 53rd Annual ASTRO Meeting Miami, USA

21. Zyla J, Papiez A, Zhao J, Qu R, Li X, Kluger Y, Polanska J, Hatzis C, Pusztai L, Marczyk M: Evaluation of zero counts to better understand the discrepancies between bulk and single-cell RNA-Seq platforms. Computational and Structural Biotechnology Journal. 2023, 21:4663-4674

22. Joanna Zyla, Rafal Dziadziuszko, Michal Marczyk, Magdalena Sitkiewicz, Magdalena Szczepanowska, Edoardo Bottoni, Giulia Veronesi, Witold Rzyman, Joanna Polanska, Piotr Widlak: miR122 and miR21 are stable components of miRNA signatures of early lung cancer after validation in three independent cohorts. Journal of Molecular diagnostics. (2024) vol. 26, nr 1, s.37-48. DOI:10.1016/j.jmoldx.2023.09.010

23. Zyla, J., Marczyk, M., Prazuch, W., Sitkiewicz, M., Durawa, A., Jelitto, M., ... & Polanska, J. (2023). Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies. Biomolecules, 14(1), 44.

24. Suwalska, A., Tobiasz, J., Prażuch, W., Socha, M., Foszner, P., Piotrowski, D., Gruszczynska, K., Sliwinska, M., Walecki, J., Popiela, T., Przybylski, G., Nowak, M., Fiedor, P., Pawlowska, M., Flisiak, R., Simon, K., Zapolska, G., Gizycka, B., Szurowska, E., Marczyk, M., Cieszanowski, A., Polanska, J. (2023). POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020–2021). Scientific Data, 10, 1–9. https://doi.org/10.1038/s41597-023-02229-5

25. Marczyk M, Fu C, Lau R, Du L, Trevarton AJ, Sinn BV, Gould RE, Pusztai L, Hatzis C, Symmans WF: Assessment of stained direct cytology smears of breast cancer for whole transcriptome and targeted messenger RNA sequencing. Cancer Cytopathology 2023, 131(5), 289- 299

26. Socha M, Prażuch W, Suwalska A, Foszner P, Tobiasz J, Jaroszewicz J, Gruszczynska K, Sliwinska M, Nowak M, Gizycka B, Zapolska G, Popiela T, Przybylski G, Fiedor P, Pawlowska M, Flisiak R, Simon K, Walecki J, Cieszanowski A, Szurowska E, Marczyk M, Polanska J: Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis. Computer Methods and Programs in Biomedicine 2023, 240, 107684

27. Sura GH, Tran K, Fu C, Du L, Marczyk M, Gould RE, Chen E, Symmans WF: Pre-Analytical Effects on Targeted and Whole Transcriptome RNA Sequencing Analysis in Cytology: The Effects of Prolonged Time in Storage of Effusion Specimens Prior to Preservation. Cytopathology 2023, 34(6), 551-561

28. Akuwudike P, López-Riego M, Marczyk M, Kocibalova Z, Brückner F, Polańska J, Wojcik A, Lundholm L: Short-and long-term effects of radiation exposure at low dose and low dose rate in normal human VH10 fibroblasts. Frontiers in Public Health 2023, 11, 1297942

29. Sura Gloria H., Tran Kevin, Fu Chunxiao, Du Lili, Marczyk Michał, Martinez Yadira, Tinnirello Agata A., Gould Rebekah E., Lau Rosanna, Symmans W. Fraser: Molecular testing opportunities on cytology effusion specimens: the pre-analytic effects of various body fluid cytology preparation methods on RNA extraction quality and targeted sequencing, Journal of the American Society of Cytopathology, Elsevier BV, vol. 12, no. 1, 2023, pp. 10-19

30. Blenman KRM, Marczyk M, Karn T, Qing T, Li X, Gunasekharan V, Yaghoobi V, Bai Y, Ibrahim EY, Park T, Silber A, Wolf DW, Reisenbichler E, Denkert C, Sinn BV, Rozenblit M, Foldi J, Rimm D, Loibl S, Pusztai L: Predictive markers of response to neoadjuvant durvalumab with nab-paclitaxel and dose dense doxorubicin/cyclophosphamide in basal-like triple negative breast cancer. Clinical Cancer Research 2022, 28 (12), p. 2587-2597.

31. Kujawa T, Marczyk M, Polanska J: Influence of single-cell RNA sequencing data integration on the performance of differentially gene expression analysis. Frontiers in Genetics 2022, 13:1009316

32. Marczyk M, Gunasekharan V, Casadevall D, Qing T, Foldi J, Sehgal R, Shan NL, Blenman KRM, O’Meara T, Umlauf S, Surovtseva YV, Muthusamy V, Rinehart J, Perry RJ, Kibbey R, Hatzis C, Pusztai L: Comprehensive analysis of metabolic isozyme targets in cancer. Cancer Research 2022, 82 (9), p. 1698–1711

33. Marczyk M, Mrukwa A, Yau C, Wolf D, Chen Y-Y, Balassanian R, Nanda R, Parker BA, Krings G, Sattar H, Zeck JC, Albain KS, Boughey JC, Liu MC, Elias AD, Clark AS, Venters SJ, Shad S, Basu A, Asare SM, Buxton M, Asare AL, Rugo HS, Perlmutter J, DeMichele AM, Yee D, Berry DA, van ’t Veer L, Symmans WF, Esserman L, Pusztai L: Treatment Efficacy Score - continuous residual cancer burden-based metric to compare neoadjuvant chemotherapy efficacy between randomized trial arms in breast cancer trials. Annals of Oncology 2022, 33 (8), p. 814-823

34. Marczyk M, Qing T, O’Meara T, Yagahoobi V, Pelekanou V, Bai Y, Reisenbichler E, Cole K, Li X, Gunasekharan V, Ibrahim E, Wei W, Fanucci K, W Wei, Rimm DL, Pusztai L, Blenman KRM: Tumor Immune Microenvironment of Self-Identified African American and Non-African American Triple Negative Breast Cancer. npj Breast Cancer 2022, 8, 88

35. Qing T, Mohsen H, Cannataro V, Marczyk M, Rozenblit M, Foldi J, Murray MF, Townsend JP, Kluger Y, Gerstein M, Pusztai L: Cancer relevance of human genes. Journal of the National Cancer Institute 2022, 114 (7), p.988-995

36. Qing T, Karn T, Rozenblit M, Foldi J, Marczyk M, Shan NL, Blenman KRM, Holtrich U, Kalinsky K, Meric-Bernstam F, Pusztai L: Molecular differences between younger versus older ER-positive HER2- negative breast cancers. npj Breast Cancer 2022, 8, 119

37. Suwalska A, Zientek L, Polanska J, Marczyk M: Quantifying Spatial Heterogeneity of Tumor‐Infiltrating Lymphocytes to Predict Survival of Individual Cancer Patients. Journal of Personalized Medicine 2022, 12, 1113

38. Fu C, Marczyk M, Samuels M, Trevarton AJ, Qu J, Lau R, Du L, Pappas T, Sinn BV, Gould RE, Pusztai L, Hatzis C, Symmans WF: “Targeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples”. BMC Cancer 2021, 114

39. Foldi J, Silber A, Reisenbichler E, Singh K, Fischbach N, Persico J, Adelson K, Katoch A, Horowitz N, Lannin D, Chagpar A, Adelson K, Park T, Marczyk M, Frederick C, Burrello T, Ibrahim E, Qing T, Bai Y, Blenman K, Rimm D, Pusztai L: Neoadjuvant durvalumab plus weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide in triple-negative breast cancer. npj Breast Cancer 2021, 7, 9

40. Patwardhan GA, Marczyk M, Wali VB, Stern DF, Pusztai L, Hatzis C: ”Treatment scheduling effects on the evolution of drug
resistance in heterogeneous cancer cell populations”. npj Breast Cancer 2021, 7, 60

41. Michal Marczyk, Joanna Polańska, Andrzej Wojcik, Lovisa Lundholm: Analysis of the applicability of microRNAs in peripheral blood leukocytes as biomarkers of sensitivity and exposure to fractionated radiotherapy towards breast cancer. International Journal of Molecular Sciences, 2021, 22(16):8705, doi: 10.3390/ijms22168705

42. Marczyk M, Macioszek A, Tobiasz J, Polanska J and Zyla J (2021) Importance of SNP Dependency Correction and Association Integration for Gene Set Analysis in Genome-Wide Association Studies. Front. Genet. 12:767358. doi:10.3389/fgene.2021.767358

43. Kimi Drobin, Michal Marczyk, Martin Halle, Daniel Danielsson, Anna Papiez, Traimate Sangsuwan, Annika Bendes, Mun-Gwan Hong, Ulrika Qundos, Mats Harm-Ringdahl, Peter Wersäll, Joanna Polanska, Jochen M. Schwenk and Siamak Haghdoost: Molecular profiling for predictors of radiosensitivity in patients with breast or head-and-neck cancer. Cancers, 2020, 12(3):753

44. Qing T, Mohsen H, Marczyk M, Ye Y, O'Meara T, Zhao H, Townsend J, Gerstein M, Hatzis C, Kluger Y, Pusztai L: "Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden". Nature Communications 2020, 11, p. 2438

45. Lau R, Du L, Chen E, Fu C, Gould R, Marczyk M, Sinn BV, Layman R, Bedrosian I, Valero V, Symmans WF: Technical validity of a customized assay of sensitivity to endocrine therapy using sections from fixed breast cancer tissue. Clinical Chemistry 2020, 66(7), p. 934–945

46. O’Meara T, Marczyk M, Qing T, Yaghoobi V, Blenman K, Cole K, Pelekanou V, Rimm DL, Pusztai L: Immunological differences between immune-rich estrogen 1 receptor-positive and immune rich triple-negative breast cancers. JCO Precision Oncology 2020, 4, p.767-779

47. Marczyk M, Patwardhan GA, Zhao J, Qu R, Li X, Wali VB, Gupta AK, Pillai MM, Kluger Y, Yan Q, Hatzis C, Pusztai L, Gunasekharan V: "Multi-Omics Investigation of Innate Navitoclax Resistance in Triple-Negative Breast Cancer Cells”. Cancers 2020, 12(9), 2551

48. Marczyk M, Jaksik R, Polanski A, Polanska J: GaMRed – adaptive filtering of high-throughput biological data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, 17(1):149-157, doi: 10.1109/TCBB.2018.2858825

49. Papiez, Anna, Michal Marczyk, Joanna Polanska, and Andrzej Polanski. "BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm." Bioinformatics, 2019, 35(11):1885.

50. Ostrowski Marcin, Marczyk Michał, Dziedzic Robert, Jelitto-Górska Małgorzata, Marjański Tomasz, Pisiak Sylwia, Jędrzejczyk Tadeusz, Polańska Joanna, Zdrojewski Tomasz, Wojtyniak Bogdan, Rzyman Witold: Lung cancer and comorbidities in lung cancer screening participants. Five-year follow-up of Gdańsk screening cohort. European Journal of Public Health, 2019, 29(6), p. 1114-7

51. Foldi J, O’Meara T, Marczyk M, Sanft T, Silber A, Pusztai L: Defining Risk of Late Recurrence in Early-Stage Estrogen Receptor–Positive Breast Cancer: Clinical Versus Molecular Tools. Journal of Clinical Oncology 2019, 37(16), p. 1365-69

52. Joanna Zyla; Michal Marczyk; Teresa Domaszewska; Stefan H.E. Kaufmann; Joanna Polanska; January Weiner: Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms. Bioinformatics, 2019, 35(24):5146-5154, doi: 10.1093/bioinformatics/btz447

53. Marczyk M, Fu C, Lau R, Du L, Trevarton AJ, Sinn BV, Gould RE, Pusztai L, Hatzis C, Symmans WF: The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues. BMC Cancer 2019, 19, 1189

54. Polanski A, Marczyk M, Pietrowska M, Widlak P, Polanska J: Initializing the EM Algorithm for Univariate Gaussian, Multi-Component, Heteroscedastic Mixture Models by Dynamic Programming Partitions, International Journal of Computational Methods, 2018, 15(3): 1850012 (21 pages), doi: 10.1142/S0219876218500123

55. Dziedzic R, Zurek W, Marjanski T, Rudzinski P, Orlowski TM, Sawicka W, Marczyk M, Polanska J, Rzyman W: Stage I non-small cell lung cancer. Long-term results of lobectomy versus sublobar resection from the Polish National Lung Cancer Registry. European Journal of Cardio-Thoracic Surgery, 2017, 52(2):363–369, doi: 10.1093/ejcts/ezx092

56. Marczyk M: Mixture modeling of 2D gel electrophoresis spots enhances the performance of spot detection. IEEE Transactions on Nanobioscience 2017, 16(2), p.91-99

57. Zyla J, Marczyk M, Weiner J, Polanska J: Ranking metrics in Gene Set Enrichment Analysis: do they matter? BMC Bioinformatics, 2017, 18(1):256, doi:10.1186/s12859-017-1674-0

58. Ros-Mazurczyk M, Jelonek K, Marczyk M, Binczyk F, Pietrowska M, Polanska J, Dziadziuszko R, Jassem J, Rzyman W, Widlak P: Serum lipid profile discriminates patients with early lung cancer from healthy controls. Lung Cancer, 2017, 112:69-74; doi:10.1016/j.lungcan.2017.07.036

59. Widlak P, Pietrowska M, Polanska J, Marczyk M, Ros M, Dziadziuszko R, Jassem J, Rzyman W: Serum mass profile signature as a biomarker of early lung cancer. Lung Cancer, 2016, 99:46-52, http://dx.doi.org/10.1016/j.lungcan.2016.06.011

60. Bobowicz M, Skrzypski M, Czapiewski P, Marczyk M, Maciejewska A, Jankowski M, Szulgo-Paczkowska A, Zegarski W, Pawlowski R, Polanska J, Biernat W, Jaskiewicz J, Jassem J: Prognostic value of 5-microRNA based signature in T2-T3N0 colon cancer. Clinical & Experimental Metastasis, 2016, 33:765–773, DOI 10.1007/s10585-016-9810-1

61. Danielsson D, Brehwens K, Halle M, Marczyk M, Sollazzo A, Polanska J, Munck-Wikland E, Wojcik A, Haghdoost S: Influence of genetic background and stress response on risk of mandibular osteoradionecrosis after radiotherapy of head and neck cancer. Head and Neck, 2016, 38(3):387-93 DOI: 10.1002/hed.23903

62. Polanski A, Marczyk M, Pietrowska M, Widlak P, Polanska J: Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry. PLOS ONE, 2015, 10(7): e0134256, doi:10.1371/journal.pone.0134256

63. Jaksik R, Marczyk M, Polanska J, Rzeszowska-Wolny J: Sources of high variance between probe signals in Affymetrix short oligonucleotide microarrays. Sensors, 2014, 14(1):532-548, doi:10.3390/s140100532

64. Jelonek K, Pietrowska M, Ros M, Zagdanski A, Suchwałko A, Polanska J, Marczyk M, Rutkowski T, Składowski K, Clench MR, Widłak P: Radiation-induced changes in serum lipidome of head and neck cancer patients. International Journal of Molecular Sciences, 2014, 15(4), p. 6609-6624, doi:10.3390/ijms15046609

65. Deperas M, Bajinskis A, Marczyk M, Polanska J, Wersall P, Lidbrink E, Ainsbury EA, Guipaud O, Benderitter M, Haghdoost S, Wojcik A: Radiation induced changes in levels of selected proteins in peripheral blood serum of breast cancer patients as a potential triage biodosimeter for large scale radiological emergencies. Health Physics, 2014, 107(6):555-563, doi:10.1097/HP.0000000000000158

66. Marczyk M, Jaksik R, Polanski A, Polanska J: Adaptive filtering of microarray expression data based on Gaussian mixture decomposition. BMC Bioinformatics 2013, 14(1):101 doi:10.1186/1471-2105-14-101

67. Pietrowska M, Polanska J, Suwinski R, Widel M, Rutkowski T, Marczyk M, Dominczyk I, Ponge L, Marczak L, Polanski A, Widlak P: Comparison of peptide cancer signatures identified by mass spectrometry in serum of patients with head and neck, lung and colorectal cancers: Association with tumor progression. International Journal of Oncology 2012, 40(1):148-156

68. Widlak P. Pietrowska M. Wojtkiewicz K. Rutkowski T. Wygoda A. Marczak Ł. Marczyk M. Polanska J. Walaszczyk A. Dominczyk I. Składowski K. Stobiecki M. Polanski A: Radiation-related changes in serum proteome profiles detected by mass spectrometry in blood of patients treated with radiotherapy due to larynx cancer. Journal of Radiation Research 2011, 52(5):575-581

69. Pietrowska M. Polanska J. Walaszczyk A. Wygoda A. Rutkowski T. Skladowski K. Marczak L. Stobiecki M. Marczyk M. Polanski A. Widlak P: Association between plasma proteome profiles analyzed by mass spectrometry, a lymphocyte-based DNA-break repair assay and radiotherapy-induced acute mucosal reaction in head and neck cancer patients. International Journal of Radiation Biology 2011, 87(7):711-719

70. Sura GH, Tran K, Fu C, Du L, Marczyk M, Martinez Y, Tinnirello AA, Gould RE, Lau R, Symmans WF: Molecular Testing Opportunities on Cytology Effusion Specimens: The Pre-Analytic Effects of Various Body Fluid Cytology Preparation Methods on RNA Extraction Quality and Targeted Sequencing – Journal of the American Society of Cytopathology 2022, in press

71. Marczyk M: Evaluation of available protein mass spectra pre-processing algorithms. Bio-Algorithms and Med-Systems 2011, 7(2):25-30

72. Wojtkiewicz K. Marczyk M. Polanska J. Polanski A. Marczak Ł. Stobiecki M. Pietrowska M. Domińczyk I. Behrendt K. Nowicka E. Tarnawski R. Widlak P: Wykorzystanie spektrometrii mas do analizy proteomu surowicy chorych na raka piersi. Onkologia Info 2010, 7(2):40-47

73. Marczyk M, Kujawa T, Papiez A, Polanska J: Single-cell transcriptomics. In Transcriptome Profiling. Progress and Prospects, Ali MA, Lee J, editors. Elsevier & Academic Press, 2023, p. 67-84 (ISBN: 978-0-323-91810-7)

74. Mrukwa, A., Marczyk, M., Zyla, J. (2022). Finding Significantly Enriched Cells in Single-Cell RNA Sequencing by Single-Sample Approaches. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L.J., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2022. Lecture Notes in Computer Science(), vol 13347. Springer, Cham. https://doi.org/10.1007/978-3-031-07802-6_3

75. Slowik, H., Zyla, J., Marczyk, M. (2022). Investigating Sources of Zeros in 10× Single-Cell RNAseq Data. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L.J., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2022. Lecture Notes in Computer Science(), vol 13347. Springer, Cham. https://doi.org/10.1007/978-3-031-07802-6_6

76. Joanna Zyla, Michal Marczyk, Joanna Polanska, W: Artificial intelligence and data processing. The monograph presenting the achievements of the Silesian University of Technology research staff / Kasprowski Paweł (red.), Monografia / Politechnika Śląska, 2022, vol. 954, Politechnika Śląska, s.377-385, ISBN 978-83-7880-859-6

77. Kalisz S, Marczyk M: Autoencoder-based bone removal algorithm from x-ray images of the lung. In IEEE 21st International Conference on Bioinformatics and Bioengineering Proceedings. BIBE 2021. (ISBN: 978-1-6654-4261-9)

78. Jozwik-Wabik P, Gładys B, Hermansa M, Macha D, Kalisz S, Strzoda T, Foszner P, Popowicz A, Marczyk M: “Removing Compression Artifacts on Whole Slide HE-stained Histopathological Images”. In Recent Advances in Computational Oncology and Personalised Medicine, Bajkacz S and Ostrowski Z, editors. COPM 2021 vol.1, p.115-125

79. Strzoda T, Kalisz S, Jozwik-Wabik P, Macha D, Hermansa M, Gładys B, Popowicz A, Foszner P, Marczyk M: “Tumor Detection on HE-stained Histopathological Images Using Deep Learning Methods: Challenges and Solutions”. In Recent Advances in Computational Oncology and Personalised Medicine, Bajkacz S and Ostrowski Z, editors. COPM 2021 vol.1, p.79-88 (ISBN 978-83-7880-800-8)

80. Marek Socha, Aleksandra Suwalska, Wojciech Prazuch, Michał Marczyk, Joanna Polanska, and POLCOVID Study Group, "UMAP-based graphic representation of POLCOVID chest X-Ray data set heterogeneity" in Recent Advances in Computational Oncology and Personalised Medicine (Eds. Ziemowit Ostrowski and Sylwia Bajkacz), 2021, vol.1, pp.100-114, ISBN 978-83-7880-800-8

81. Marczyk M: Processing 2D Gel Electrophoresis Images for Efficient Gaussian Mixture Modeling. In 11th International Conference on Practical Applications of Computational Biology & Bioinformatics. PACBB 2017. Advances in Intelligent Systems and Computing, vol 616, Fdez-Riverola F, Mohamad M, Rocha M, De Paz J, Pinto T, editors. Springer, Cham 2017, p. 35-42 (ISBN: 978-3-319-60815-0)

82. Marczyk M, Smejkal T: Spatial Feature Selection For Finding Biomarkers Using Imaging Mass Spectrometry Data. In Proceedings of the XXIII National Conference on Applications of Mathematics in Biology and Medicine, p. 123-129 (ISBN: 978-83-932893-3-2)

83. Polanski A, Marczyk M, Pietrowska M, Widlak P, Polanska J: Least squares estimators of peptide species concentrations based on Gaussian mixture decompositions of protein mass spectra. 12th German-Polish Workshop on Stochastic Models, Statistics and Their Applications, SMSTA 2015, 16-20.02.2015, Wrocław, Poland. Proceedings in Mathematics and Statistics, vol.122, pp 425-432, ISBN 978-3-319-13880-0 Eds. Steland A, Rafajłowicz E, Szajowski K. Springer

84. Krukiewicz Katarzyna, Marczyk Michał, Ostrowski Ziemowit, Polańska Joanna: (eds.)Computational oncology and personalized medicine - crossing borders, connecting science. COPM2023, Gliwice, April 26th, 2023. Book of abstracts. Conference programme, 2023, Politechnika Śląska