DNA sequencing remains one of the most important problems in molecular and computational biology. One of the methods used for this purpose is sequencing by hybridization. In this approach usually DNA chips composed of a full library of oligonucleotides of a given length are used, but in principle it is possible to use another types of chips. Isothermic DNA chips, being one of them, when used for sequencing may reduce hybridization error rate. However, it was not clear if a number of errors following from subsequence repetitions is also reduced in this case. In this paper a method for estimating resolving power of isothermic DNA chips is described which allows for a comparison of such chips and the classical ones. The analysis of the resolving power shows that the probability of sequencing errors caused by subsequence repetitions is greater in the case of isothermic chips in comparison to their classical counterparts of a similar cardinality. This result suggests that isothermic chips should be chosen carefully since in some cases they may not give better results than the classical ones.
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.