Human leukocyte antigen (HLA) typing

HLA locus is involved in the mechanisms of tumor tolerance and diagnosis. The HLA class I and class II genotyping along with expression analysis are currently one of the most promising clinical approaches.

Neoantigens prediction and vaccines design

Tumour neoantigens are crucial for immune response to immunotherapy. Identification, scoring and indication neoantigens that induce the strongest immune response, excluding false positives ones is encouraging direction to design personalized cancer vaccines.

Somatic and germline mutations

Reliable identification of somatic and germline mutations is an essential element of cancer genome research and patients' molecular diagnostics.

Multilevel expression analysis

Integration of multiple sequencing technologies leveraged by machine learning technology increases statistical power to detect novel mutations, especially in low purity tumours.

Identification and characterization of functional lncRNAs

Long non-coding RNAs play a crucial role in regulatory biology. They can act as a regulatory factors essential for tumour and microbiome biology. We identify potential lncRNAs and apply machine learning to predict the effects of its mutations.

Molecular Modelling and Computational Biology

Molecular modelling encompasses all methods, theoretical and computational, used to model or mimic the behaviour of molecules. The methods are used in computational biology to study molecular systems ranging from small chemical systems to large biological molecules.

Computer Aided Drug Design (CADD)

Computer-aided drug design includes computational chemistry, molecular modelling, molecular design and rational drug design. Our original in-house tools and knowledge leaded to therapeutic molecules currently being under the last phase of clinical trial.