Julita Machlowska, PhD
PhD, Jagiellonian University, Medical University of Lublin
Post-doc
High-Throughput Single-Cell RNA and ATAC Sequencing
Description
Dr. Julita Machlowska obtained her Master of Science degree in Biotechnology in 2010 at the Jagiellonian University and a PhD degree in Medical Sciences in 2020 at the Medical University of Lublin. In 2012-2017 she worked in Center for Medical Genomics – OMICRON, where she developed her skills in a next generation sequencing. Dr. Machlowska is an author of four reviews and seven original papers (https://www.scopus.com/authid/detail.uri?authorId=57073862000)
Dr Machlowska’s major task in CGG is to perform high-throughput single-cell RNA and ATAC sequencing to address fundamental questions in eye research.
Publication list
- AH Ludwig-Słomczyńska, MT Seweryn, P Radkowski, P Kapusta, J Machlowska, S Pruhova, D Gasperikova, C Bellanne-Chantelot, A Hattersley, B Kandasamy, L Letourneau-Freiberg, L Philipson, A Doria, PP Wołkow, MT Małecki, T Klupa. Variants influencing age at diagnosis of HNF1A-MODY. Mol Med., 28(1):113, (2022)
- J Machlowska, P Kapusta, M Szlendak, A Bogdali, F Morsink, P Wołkow, R Maciejewski, GJA Offerhaus, R Sitarz. Status of CHEK2 and p53 in patients with early-onset and conventional gastric cancer. Oncol Lett., 21(5):348, (2021)
- J Machlowska, P Kapusta, J Baj, FHM Morsink, P Wołkow, R Maciejewski, GJA Offerhaus, R Sitarz. High-Throughput Sequencing of Gastric Cancer Patients: Unravelling Genetic Predispositions Towards an Early-Onset Subtype. Cancers (Basel), 12(7):1981, (2020)
- J Machlowska, J Baj, M Sitarz, R Maciejewski, R Sitarz. Gastric Cancer: Epidemiology, Risk Factors, Classification, Genomic Characteristics and Treatment Strategies. Int J Mol Sci., 21(11):4012, (2020)
- J Totoń-Żurańska, P Kapusta, M Rybak-Krzyszkowska, K Lorenc, J Machlowska, A Skalniak, E Filipek, D Pawlik, PP Wołkow. Contribution of a Novel B3GLCT Variant to Peters Plus Syndrome Discovered by a Combination of Next-Generation Sequencing and Automated Text Mining. Int J Mol Sci., 20(23):6006, (2019)
- AM Borys, M Seweryn, T Gołąbek, Ł Bełch, A Klimkowska, J Totoń-Żurańska, J Machlowska, P Chłosta, K Okoń, PP Wołkow. Patterns of gene expression characterize T1 and T3 clear cell renal cell carcinoma subtypes. PLoS One., 14(5):e0216793, (2019)
- J Machlowska, M Pucułek, M Sitarz, P Terlecki, R Maciejewski, R Sitarz. State of the art for gastric signet ring cell carcinoma: from classification, prognosis, and genomic characteristics to specified treatments. Cancer Manag Res., 11:2151-2161, (2019)
- S Borys, AH Ludwig-Slomczynska, M Seweryn, J Hohendorff, T Koblik, J Machlowska, B Kiec-Wilk, P Wolkow, MT Malecki. Negative pressure wound therapy in the treatment of diabetic foot ulcers may be mediated through differential gene expression. Acta Diabetol., 56(1):115-120, (2019)
- A Jabrocka-Hybel, A Skalniak, J Piątkowski, R Turek-Jabrocka, P Vyhouskaya, A Ludwig-Słomczyńska, J Machlowska, P Kapusta, M Małecki, D Pach, M Trofimiuk-Müldner, K Lizis-Kolus, A Hubalewska-Dydejczyk. How much of the predisposition to Hashimoto’s thyroiditis can be explained based on previously reported associations? J Endocrinol Invest., 41(12):1409-1416, (2018)
- M Pucułek, J Machlowska, R Wierzbicki, J Baj, R Maciejewski, R Sitarz. Helicobacter pylori associated factors in the development of gastric cancer with special reference to the early-onset subtype. Oncotarget., 9(57):31146-31162, (2018)
- J Machlowska, R Maciejewski, R Sitarz. The Pattern of Signatures in Gastric Cancer Prognosis. Int J Mol Sci., 19(6):1658, (2018)
- M Szopa, AH Ludwig-Galezowska, P Radkowski, J Skupien, J Machlowska, T Klupa, P Wolkow, M Borowiec, W Mlynarski, MT Malecki. A family with the Arg103Pro mutation in the NEUROD1 gene detected by next-generation sequencing – Clinical characteristics of mutation carriers. Eur J Med Genet., 59(2):75-9, (2016)
Research projects
Research groups
We are interested in creating new approaches for comprehensive inference of developmental trajectories and delineation of cell atlases from single-cell data, understanding the role of cell-to-cell signaling and biological pathways in lineage commitment and transitions between cellular states.
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