Publications by authors named "Evgeny D Petrovskiy"

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals.

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Molecular genetic processes generally involve proteins from distinct intracellular localisations. Reactions that follow the same process are distributed among various compartments within the cell. In this regard, the reaction rate and the efficiency of biological processes can depend on the subcellular localisation of proteins.

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Background: An important issue in the target identification for the drug design is the tissue-specific effect of inhibition of target genes. The task of assessing the tissue-specific effect in suppressing gene activity is especially relevant in the studies of the brain, because a significant variability in gene expression levels among different areas of the brain was well documented.

Results: A method is proposed for constructing statistical models to predict the potential effect of the knockout of target genes on the expression of genes involved in the regulation of apoptosis in various brain regions.

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Article Synopsis
  • This study introduces a new method called mosaic network modelling, which combines independent mathematical models of gene regulatory networks to better understand complex biological systems, even when detailed interaction data is lacking.* -
  • The approach utilizes control theory and ordinary differential equations to model dynamics effectively, achieving less than 10% deviation from initial model behaviors in over 10,000 simulated networks.* -
  • The method was applied to create a mosaic gene regulatory network that integrates the hepatitis C virus (HCV) with pathways related to tumor necrosis factor (TNF)-induced apoptosis and NF-κB induction, showcasing its practical utility.*
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Background: Biological processes are usually distributed over various intracellular compartments. Proteins from diverse cellular compartments are often involved in similar signaling networks. However, the difference in the reaction rates between similar proteins among different compartments is usually quite high.

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In vivo proton magnetic resonance spectroscopy ((1) H MRS) of outbred stock ICR male mice (originating from the Institute of Cancer Research) was used to study the brain (hippocampus) metabolic response to the pro-inflammatory stimulus and to the acute deficiency of the available energy, which was confirmed by measuring the maximum oxygen consumption. Inhibition of glycolysis by means of an injection with 2-deoxy-d-glucose (2DG) reduced the levels of gamma-aminobutyric acid (GABA, p < 0.05, in comparison with control, least significant difference (LSD) test), N-acetylaspartate (NAA, p < 0.

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