- Head of laboratory
- Scientific Staff
- PhD Students
- Research profile
- Core facility activities
- Current research activities
- Recent publications
Head of laboratory
The mission of our laboratory is to provide world-class bioinformatics support to experimental groups at the Nencki Institute. The main form of our activity are collaborative projects with experimental groups, in which we are responsible for the bioinformatics part. Our own research interests include regulatory genomics, statistical inference, dynamic systems and molecular dynamics of proteins and macromolecular complexes.
Core facility activities
- Support of high-throughput methods: genomics, transcriptomics, proteomics; pre-processing, statisticalanalysis, functionalanalysisandvisualization.Currently5projects (4–protein mass spectrometry data, 1 – genomic data); from neurobiology, bioenergetics and neurooncology domains; in collaborationwith 5 research groups at the Nencki Institute.
- Statistical analysis and visualization ofmulti-dimensional data. Currently 4 projects; one in collaboration with the Laboratory of Neuroplasticity – integrating protein, mRNA and metabolite data for several brain structures and ages of animals; and 3 in collaborationwith the Laboratory of Bioenergetics and Biological Membranes – combining biochemical, microscopic and functional data.
- Analysis of gene regulatory regions andmaintenance of the Nencki Genomics Database. Currently 2 projects; in the context of leukaemia/cancer; in collaboration with the Laboratory of Cytometry and the Laboratory of Signal Transduction.
- Molecular dynamics simulations of proteins with known 3D structure: preparation, simulations andanalysis of trajectories.Currently 5projects; inthe oncology andmyopathies domain; in collaboration with 4 research groups at the Nencki Institute.
Current research activities
- Analysis of open chromatin landscape in classically and alternatively activatedmicroglia. In collaboration with the Laboratory of Molecular Neurobiology.
- Modeling of the dynamics of interactions between selected miRNA and transcription factors in cell response to stress. In collaboration with the Medical University of Gdańsk.
- Bioinformatics identification of functional regulatory mutations and their target genes in headandneck carcinoma. Incollaborationwiththe InstituteofHumanGenetics, PAS, Poznań.
- Interactions of ABeta-42 with small peptides that block its toxicity. Design of novel ABeta42 inhibitors. In collaboration with the Laboratory of Molecular Basis of Cell Motility and the Sanford Burnham Prebys Medical Discovery Institute, La Jolla, USA.
- Mechanisms ofmotion generation bymolecularmotors. In collaboration with the Laboratory of Molecular Motors.
- Design of inhibitors of the thymidylate biosynthesis cycle and of the human dihydrofolate reductase and thymidylate synthase complex. In collaboration with the Faculty of Chemistry,WarsawTechnical University.
Nagaraj S., Laskowska-Kaszub K., Dębski K.J., Wojsiat J., Dąbrowski M., Gabryelewicz T., Kuźnicki J., Wojda U. (2017) Proﬁle of 6 microRNA in blood plasma distinguish early stage Alzheimer’s disease patients from non-demented subjects. Oncotarget, doi:10.18632/oncotarget.15109.
Ellert-Miklaszewska A., Wiśniewski P., Kijewska M., Gajdanowicz P., Pszczółkowska D., Przanowski P., Dąbrowski M., Maleszewska M., Kamińska B. (2016) Tumour-processed osteopontin and lactadherin drive the protumorigenic reprogramming of microglia and glioma progression. Oncogene, 35(50): 6366-6377.
Bednarczyk J., Dębski K.J., Bot A.M., Łukasiuk K. (2016) MBD3 expression and DNA binding patterns are altered in a rat model of temporal lobe epilepsy. Sci Rep, 6: 33736.
Antosiewicz A., Jarmuła A., Przybylska D., Mosieniak G., Szczepanowska J., Kowalkowska A., Rode W., Cieśla J. (2016) Human dihydrofolate reductase and thymidylate synthase form a complex in vitro and co-localize in normal and cancer cells. J Biomol Struct Dyn, 5: 1-17.
Dąbrowski M., Dojer N., Krystkowiak I., Kamińska B., Wilczyński B. (2015) Optimally choosing PWM motif databases and sequence scanning approaches based on ChIP-seq data. BMC Bioinformatics, 16: 140.