What we actually do

The main areas of our research are: DNA sequencing and assembling (including design of algorithms for the NGS sequencers); protein structure analysis; RNA structure analysis and prediction (including automatic tertiary structure prediction tool); nanotechnology and DNA computing.

Viral infection modeling
HCV is one of the most prevalent human pathogens, infecting more than 170 million people worldwide. Similar to other RNA-based viruses, it exists as a quasispecies in an individual organism, i.e. as a pool of phylogenetically related but genetically slightly distinct variants. With its capacity for long-lasting persistence in the host, HCV causes chronic infections that can lead to liver fibrosis, cirrhosis and hepatocellular carcinoma.

We investigate a correlation between genetic diversity of hepatitis C virus population and the level of viral RNA accumulation in patient blood. Genetic diversity is defined as the mean Hamming distance between all pairs of virus RNA sequences representing the population. We have found that a low Hamming distance (i.e. low genetic diversity) correlates with a high RNA level; symmetrically, high diversity corresponds to a low RNA level. In our opinion the obtained correlation strength justifies the use of the viral RNA level as a measure enabling prediction of efficiency of an established therapy.

Structure of the IRES located in the 5'-UTR of HCV[source]