The main topics of the workshop discussion were: medical systems biology, signaling and cellular regulation, new mathematical methods and algorithms, host-pathogen interactions.
From the side of Institute of Cytology and Genetics SB RAS together with PBSoft Nikita Ivanisenko made an oral presentation on: "A stochastic model for suppression of subgenomic hepatitis C virus replication in Huh-7 cells".
The report was devoted to the developed for the first time mathematical model for subgenomic HCV replicon replication in Huh-7 cells in the presence of the HCV NS3 protease inhibitors. The developed stochastic model describes the experimental kinetics of the viral RNA suppression during an observation time of up to 15 days. The model takes into account the fact that mutant drug-resistant replicons preexist in a treatment-naïve replicon population, also the stochastic nature of the replication-degradation of viral RNA. When disregarding the stochastic of the replication-degradation of viral RNA, the model is still able to describe the experimental kinetics during the initial few days action of the inhibitors when cellular concentration of viral RNA is rather high (≥ 20 RNA molecules/cell).
In the model was used a simplified scheme of subgenomic HCV replicon replication in Huh-7 cells in the presence of inhibitors, also a minimal number of parameters. The novelties were vesicles of two types, one producing mutant RNAs, the other RNA of wild-type into the cytoplasm. Computational analysis of the model have shown that the stochastic nature of the subgenomic HCV replicon replication and the drug-resistant mutant replicons in cells is necessary for the understanding of the experimentally observed biphasic reduction of viral RNA in the presence of the inhibitors.
Also two poster presentations were made by the head of PBSoft Dr. Vladimir Ivanisenko.
The first poster: "Reconstruction of the associative genetic networks based on integration of automated text-mining methods and protein-ligand interactions prediction" was devoted to the prototype of the interactive text-mining system (ITMSys) developed by PBSoft for the automated reconstruction of associative genetic network based on the interactive analysis of scientific literature and protein-ligand interactions prediction. The ITMSys software is equipped with tools for reconstruction, visualization of gene networks, prediction of a new interactions and web-based interface. The system ensures analysis of the full-text articles of the scientific publications with the representation of the results in the form of genetic networks. These tool can be used by experts for the acceleration of genetic mnetworks reconstruction process, as well as in the other fields of science related automated analysis of scientific literature.
The second poster: "Associative network discovery system (ANDSYSTEM): automated literature mining tool for extracting relationships between diseases, pathways, proteins, genes, micrornas and metabolites" was deducated to the innovative software tool and uniq text mining aproach for the automated high-quality extraction of knowledge from the texts of the scientific publications developed within the Company that were used towards the SysPatho tasks. The ANDSystem was developed for the purpose of scanning literature relationships between diseases, pathways, genes, microRNAs and metabolites. The ANDSystem incorporates utilities for the automated extraction of knowledge from Pubmed published scientific texts and analysis of factographic databases. The ANDCell database contains information on molecular-genetic events retrieved from scientific literature and databases. The ANDVisio is a user's interface to the ANDCell database stored on the remote server, it provides graphic visualization, editing and search features as well as possibilities for saving of associative gene networks in various formats resulting from user's requests. The ANDVisio is provided with various tools that support filtering by object types, relationships between objects and information sources; graph layout; search of the shortest pathway; cycles in graphs.
The ANDSystem can assist in the interpretation of complex multifactorial experimental data. In Particular, the ANDSystem was used for the analysis of proteomic experimental data. For example, with the help of ANDSystem networks of molecular and genetic interactions of proteins of Helicobacter pylori, differentially expressed in different strains isolated from patients with chronic gastritis and gastric tumors were reconstructed. On the example of the establishment of interactions between human proteins and proteins of hepatitits C virus was shown a high accuracy of the method of knowledge extraction from texts.