@ARTICLE{Kędziora_P._Computational_2005,
 author={Kędziora, P. and Figlerowicz, M. and Formanowicz, P. and Alejska, M. and Jackowiak, P. and Malinowska, N. and Frątczak, A. and Błażewicz, J.},
 volume={vol. 53},
 number={No 3},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={273-281},
 howpublished={online},
 year={2005},
 abstract={Despite the considerable progress that has recently been made in medicine, the treatment of viral infections is still a problem remaining to be solved. This especially concerns infections caused by newly emerging patogenes such as: human immunodeficiency virus, hepatitis C virus or SARS-coronavirus. There are several lines of evidence that the unusual genetic polymorphism of these viruses is responsible for the observed therapeutic difficulties. In order to determine whether some parameters describing a very complex and variable viral population can be used as prognostic factors during antiviral treatment computational methods were applied. To this end, the structure of the viral population and virus evolution in the organisms of two patients suffering from chronic hepatitis C were analyzed. Here we demonstrated that phylogenetic trees and Hamming distances best reflect the differences between virus populations present in the organisms of patients who responded positively and negatively to the applied therapy. Interestingly, the obtained results suggest that based on the elaborated method of virus population analysis one can predict the final outcome of the treatment even before it has started.},
 type={Artykuły / Articles},
 title={Computational methods in diagnostics of chronic hepatitis C},
 URL={http://journals.pan.pl/Content/111775/PDF-MASTER/(53-3)273.pdf},
 keywords={RNA sequence analysis, phylogenetic trees, combinatorial methods, hepatitis C virus, chronic hepatitis C diagnostics, interferon alpha and ribavirin therapy},
}