Research Areas

The MEDGENET project will focus on the following research areas.

Application of Next-Gen Sequencing technologies (WGS, WES, RNA-seq):

  • Designing the NGS;
  • Description of genomic landscape of chronic lymphocytic leukemia (CLL);
  • Genomic analysis of genom, exome sequencing, along with targeted ultra-deep sequencing.

Bioinformatics and Data Analysis:

  • Application of bioinformatical approaches and techniques for structural variant detection in tumours, especially, purpose-built bioinformatics and biostatistics tools and workflows;
  • Using life science software development for analysis of biomolecular structural patterns.

Genome instability and telomere maintenance in tumor cells:

  • Analysis of genomic instability in tumor cells (on example of leukemic B-lymphocytes);
  • Studying the architecture, activities and evolution of SMC complexes.

Role of RNA processing and small non-coding RNAs:

  • Studying the role of RNA modifications in the innate immune system;
  • Studying genetic defects, in particular mRNA slicing, mRNA-processing and transcriptional elongation;
  • Transcriptional regulation by non-coding RNAs.

Quantitative analyses of biomolecules:

  • Investigating the behavior of particular proteins and enzymes in living organisms.

Immune cells profiling:

  • Studying high-throughput immonoprofiling;
  • Establishing a complete bioinformatics pipeline to accurately and efficiently capture, study and score immunoprofiles;
  • Biomedical studies in the field of adaptive immunity.

Prognostic and predictive biomarkers:

  • Identification of potential susceptibility mechanisms, reveal novel diagnostic, prognostic, and predictive biomarkers, as well as new therapeutic targets in tumor tissue;
  • Discover novel biomakers applicable in cancer diagnostics.

Targeted therapy and treatment response monitoring:

  • Investigations of novel targeted therapy options and introduction of personalized medicine.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 692298.
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