Advanced studying the formation of stable secondary DNA structures as applied to DNA technologies

DNA oligonucleotides are essential components of a high number of technologies in molecular biology which are based on DNA and RNA hybridization. Such DNA hybridization-based experimental methods as multiplex polymerase chain reaction, microarray analysis, NanoString multiplex analysis, next-generation targeted sequencing, and similar approaches require the use of complex mixtures of oligonucleotides (primers and probes) in one tube. Single-stranded DNA molecules also tend to bind to themselves. The probability of such nonspecific binding increases depending on the degree of analysis complexity. Moreover, there is a necessity to revise existing approaches to the development of certain hybridization probes and primers for existing DNA detection technologies. First of all, it is necessary for such technologies as standard or quantitative PCR with various DNA amplification methods for the detection of a specific amplicon using hybridization probes, as well as for isothermal DNA amplification methods that combine many nested primers and fluorescent probes. Revision is needed to accurately determine the melting temperature for both complementary DNA duplexes and DNA duplexes with the presence of non-complementary bases through the use of machine learning methods.

The main objective of the project is to conduct study of stable secondary structures of nucleic acids based on experimental data on DNA/DNA hybridization for complex single-stranded DNA mixtures using a machine learning approach. The development of bioinformatics tools that implement machine learning approaches for calculating the basic thermodynamics of secondary DNA structures as applied to DNA detection and amplification technologies.