{"id":18040,"date":"2022-08-10T16:30:11","date_gmt":"2022-08-10T09:30:11","guid":{"rendered":"https:\/\/bgrssb.icgbio.ru\/2022\/?page_id=18040"},"modified":"2024-09-18T16:29:08","modified_gmt":"2024-09-18T09:29:08","slug":"video-of-reports","status":"publish","type":"page","link":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/video-of-reports\/","title":{"rendered":"\u0412\u0438\u0434\u0435\u043e\u0437\u0430\u043f\u0438\u0441\u0438 \u0434\u043e\u043a\u043b\u0430\u0434\u043e\u0432"},"content":{"rendered":"\n\n\n\n\t\n\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t
Presenter<\/th>Topic<\/th>Section<\/th>\n<\/tr>\n<\/thead>\n
Akhmetzianova L.<\/td>Design primers for LAMP \u2013 Amplification<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Babak O.<\/td>Relationship Patterns of the Genetic Regulation of Carotenoid and Flavonoid Accumulation in Tomato Fruits (S. lycopersicum)<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Kapusta A.<\/td>stLFR a Novel Approach to Genome Assembly<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Krasikova A.<\/td>Chicken oocyte transcriptome: RNAseq of nuclear and cytoplasmic long and short RNAs<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Maslov D.<\/td>Insights into Opisthorchis felineus genome organization.<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Petrushin I.<\/td>Diversity of CRISPR arrays identified into plant mitochondrial genomes<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Pronozin A.<\/td>ICAnnoLncRNA: automatic pipeline of identification, classification and annotation of long noncoding RNAs.<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Shevchenko A.<\/td>Post-stress changes in the gut microbiota in rat strains with different excitability of the nervous system.<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Vodiasova E.<\/td>Characterization of the glutathione S-transferase gene family in Mollusca<\/a><\/td>1.1 Genomics and transcriptomics of plants and animals<\/td>\n<\/tr>\n
Bezuglov V.<\/td>ITAS: integrated transcript annotation for small RNA<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Gromyko D.<\/td>Promoter motif inference and annotation of promoter sequences in bacterial genomes based on the analysis of structures of alternative sigma factor-promoter complexes<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Korobeynikova A.<\/td>Lymphocyte migration factors in breast cancer: a transcriptome analysis<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Levitsky V.<\/td>Web-MCOT server for motifs co-occurrence search in ChIP-seq data<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Matveenko A.<\/td>Amplification of the release factor genes as a mechanism of adaptation in yeast<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Sergushichev A.<\/td>GESECA: Gene Set Co-regulation Analysis<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Tsukanov A.<\/td>enRest tool for transcription factor binding sites overrepresentation analysis in RNA-seq data<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Zhurakovskaya A.<\/td>\u0410ctin genes of the White Sea sponge Halisarca dujardinii: structure and regulation<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Kabirova E.<\/td>Influence of TADs boundary disruption on 3D genome organisation and genes expression at the mouse Pdgfra\/Kit\/Kdr locus<\/a><\/td>1.3 Functional and applied 3D genomics<\/td>\n<\/tr>\n
Lukyanchikova V.<\/td>Insights into the 3D-genome organization in malaria mosquitoes<\/a><\/td>1.3 Functional and applied 3D genomics<\/td>\n<\/tr>\n
Maslova A.<\/td>Chromosome structural variations of the chicken erythroblast HD3 cell line identified by Hi-C<\/a><\/td>1.3 Functional and applied 3D genomics<\/td>\n<\/tr>\n
Myakinkov I.<\/td>Development of a mESC line for studying the condensin II influence on interphase 3D genome organization<\/a><\/td>1.3 Functional and applied 3D genomics<\/td>\n<\/tr>\n
Ryumina E.<\/td>Higher order chromatin structure: new insight with novel correlative approach<\/a><\/td>1.3 Functional and applied 3D genomics<\/td>\n<\/tr>\n
Anashkina A.<\/td>Textual and Structural Analysis of RNA Polymerase II Core Promoter of Evolutionary Diverse Organisms<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Daugavet M.<\/td>Bacteriophages as vectors of gene transfer from prokaryotes to eukaryotes<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Gorshkova T.<\/td>Transcriptomics as an effective tool to study plant cell wall formation and function<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Kozlov A.<\/td>The carcino-evo-devo theory as a unified theory of biological developmen<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Lachynova M.<\/td>Development and application of a computational pipeline to analyze genes encoding phospholipase domains in flatworms<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Proskuryakova A.<\/td>Chromosome evolution in Ruminantia<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Pushmina E.<\/td>Analysis of environment adaptation features of the bacteria of Flavobacterium family by comparative genomics<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Saranchina A.<\/td>Genetic variety of Baikal endemic amphipods (Crustacea: Amphipoda) Eulimnogammarus verrucosus (Gerstf., 1858) in the Angara river<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Volobueva M.<\/td>Classification of prokaryotic DNA methyltransferases by sequence similarity of the catalytic domain<\/a><\/td>1.4 Evolutionary genomics, bioinformatics, and molecular phylogeny<\/td>\n<\/tr>\n
Khristichenko M.<\/td>Computation and tracing of periodic solutions of Marchuk-Petrov model<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of biological systems<\/td>\n<\/tr>\n
Mustafin Z.<\/td>Evolutionary analysis of gene networks with Orthoweb software<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of biological systems<\/td>\n<\/tr>\n
Neganova I.<\/td>Creation of the mathematical model for the prognostic analysis of human pluripotent stem cells based on their morphological portrait.<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of biological systems<\/td>\n<\/tr>\n
Ivanisenko V.<\/td>ANDSystem: cognitive computer system for automated gene networks reconstruction and analysis<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of biological systems<\/td>\n<\/tr>\n
Logofet D.<\/td>Alpine resort or battle for survival: A didactic story about short-lived perennials and their matrix models<\/a><\/td>2.2 Modeling of population and ecological systems and processes<\/td>\n<\/tr>\n
Shubin A.<\/td>Application of convolutional neural networks in the processing of hemispherical photos of the canopy<\/a><\/td>2.2 Modeling of population and ecological systems and processes<\/td>\n<\/tr>\n
Mishin A.<\/td>Overview of lipid-sensing GPCR receptors structure and function<\/a><\/td>3.1 The role of synchrotron radiation and advanced instrumental techniques for macromolecular crystallography and pharmacology<\/td>\n<\/tr>\n
Akimov S.<\/td>Statistical approach to regulation of membrane-permeabilizing activity of antimicrobial peptides<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Anashkina A.<\/td>Hierarchical Structure of Protein Sequences \u2013 New Insight of Protein Organization<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Efremov R.<\/td>\u201cDynamic molecular portraits\u201d of biomembranes: a computational insight.<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Galzitskaya O.<\/td>Study of membrane permeability for various peptides by steered molecular dynamics<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Kuzmin A.<\/td>Structure and dynamics of the SARS-CoV-2 envelope protein<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Lyapina E.<\/td>Allosteric ligand subpocket of S1P5 as a determinant of inverse agonism and ligand specificity<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Sokolova O.<\/td>Use of lipodiscs in structural studies of ion channels<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Volynsky P.<\/td>Identification of factors important for the translocation of water-soluble proteins across the membrane using computer simulations<\/a><\/td>3.2 Structural biology of proteins and membranes<\/td>\n<\/tr>\n
Biziukova N.<\/td>Identification of virus-host interaction mechanisms based on text-mining approach<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Karasev D.<\/td>Predicting the protein-ligand interactions based on ligands\u2019 structures and proteins\u2019 sequences<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Poroikov V.<\/td>Drug repurposing for COVID-19 therapy: challenges and opportunities<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Serebrennikova M.<\/td>Development of a searching algorithm for new cell-penetrating peptides based on machine learning methods<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Sukhachev V.<\/td>Prediction of adverse effects of drug-drug interactions on the cardiovascular system based on the analysis of structure-activity relationships<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Tabassum S.<\/td>Network Pharmacology and Molecular Docking Techniques to Elucidate the Mechanisms of Ocimum Sanctum against Tuberculosis<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Tarasova O.<\/td>Computational Analysis of Viral Drug Resistance and Treatment Efficacy: Case study for HIV-infection<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Zavestovskaya I.<\/td>Nanoteranostics based on multimodal nanoparticles and nanosystems<\/a><\/td>3.3 Chemoinformatics and chemical biology<\/td>\n<\/tr>\n
Bragina E.<\/td>Understanding the role of genetics in comorbidity<\/a><\/td>4.1 Human medical\/population genomics and genetics<\/td>\n<\/tr>\n
Bushueva O.<\/td>Molecular mechanisms of cardio- and cerebrovascular comorbidity: from experimental analysis of structural and epigenetic variations in the human genome to post-GWAS analysis of genetic correlations between diseases<\/a><\/td>4.1 Human medical\/population genomics and genetics<\/td>\n<\/tr>\n
Kharkov V.<\/td>Detailed phylogeny of the Y-chromosome haplogroup N1a2 in the populations of Siberia and Eastern Europe<\/a><\/td>4.1 Human medical\/population genomics and genetics<\/td>\n<\/tr>\n
Ponomarenko M.<\/td>Bioinformatics search for genetic markers of socially significant diseases in promoters of human genes<\/a><\/td>4.1 Human medical\/population genomics and genetics<\/td>\n<\/tr>\n
Savvina M.<\/td>DNA-microarray as an alternative diagnostic tool for targeted genetic carrier screening in population of Yakut ethnic group<\/a><\/td>4.1 Human medical\/population genomics and genetics<\/td>\n<\/tr>\n
Shnaider T.<\/td>Investigation of the mechanisms of neurodevelopmental disorders caused by mutations in the CNTN6 gene on the cerebral organoids model<\/a><\/td>4.1 Human medical\/population genomics and genetics<\/td>\n<\/tr>\n
Belonogova N.<\/td>Association of PANX3 with chronic back pain discovered using gene-based analysis<\/a><\/td>4.2 Genome-wide association studies<\/td>\n<\/tr>\n
Elgaeva E.<\/td>Bidirectional Mendelian randomization study reveals causal effects of psychosocial factors on chronic back pain and vice versa<\/a><\/td>4.2 Genome-wide association studies<\/td>\n<\/tr>\n
Loboda A.<\/td>A platform for case-control matching enables association studies without genotype sharing<\/a><\/td>4.2 Genome-wide association studies<\/td>\n<\/tr>\n
Nedoluzhko A.<\/td>Ancient DNA analysis of mummies from the post-Scythian Oglakhty cemetery in South Siberia.<\/a><\/td>4.3 Human origin and evolution<\/td>\n<\/tr>\n
Kovtun A.<\/td>Bioinformatics approaches and methods for analysis of gut microbiota<\/a><\/td>5.1 Biotechnology through the prism of microbiome<\/td>\n<\/tr>\n
Panikov N.<\/td>Genome-scale reconstructions of microbial biodynamics great expectations<\/a><\/td>5.1 Biotechnology through the prism of microbiome<\/td>\n<\/tr>\n
Sonets I.<\/td>Investigating bacterial and yeast diversity of spontaneous fermentation beer and cider using Hi-C metagenomics<\/a><\/td>5.1 Biotechnology through the prism of microbiome<\/td>\n<\/tr>\n
Zakhartsev M.<\/td>On the system-biological approach in modern C1-biotechnological research<\/a><\/td>5.1 Biotechnology through the prism of microbiome<\/td>\n<\/tr>\n
Afonnikova S.<\/td>Comparative and evolution genomics of somatic antigens of Oxalobacteraceae family<\/a><\/td>5.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Babich T.L.<\/td>Diversity and possible metabolic activity of the microbial community in nitrate- and radionuclide-contaminated groundwater<\/a><\/td>5.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Dedysh S.<\/td>Methanotroph diversity in natural and anthropogenic habitats as an inexhaustible source of novel biotechnologically relevant strains<\/a><\/td>5.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Ershov A.<\/td>Halophilic bacteria of the genera Halomonas and Marinobacter from petroleum reservoirs and their possible applications in biotechnology<\/a><\/td>5.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Litti Y.<\/td>Effect of organic loading rate on the biohythane production in the continuous two-stage anaerobic digestion of confectionery wastewater<\/a><\/td>5.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Mikhaylova Y.<\/td>Whole-genome analysis of Staphylococcus aureus isolates from ready-to-eat food<\/a><\/td>5.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Morozov A.<\/td>Elusive recurrent bacterial contamination in a diatom culture: a case study<\/a><\/td>5.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Kabardin I.<\/td>Development of optical and ultrasound methods for the multi-phase flows investigation and numerical calculations verification in biotechnological process<\/a><\/td>5.3 Industrial biotechnologies: creation of producer strains<\/td>\n<\/tr>\n
Moskalensky A.<\/td>A device reporting cell culture growth in CO2 incubator via Bluetooth<\/a><\/td>5.3 Industrial biotechnologies: creation of producer strains<\/td>\n<\/tr>\n
Sheremetieva M.<\/td>Metabolic engineering of corynebacteria to create a producer of L-valine<\/a><\/td>5.3 Industrial biotechnologies: creation of producer strains<\/td>\n<\/tr>\n
Stavrovskaya A.<\/td>Bioinformatics and experimental approaches in the creation of the drug \u201cSuperbact\u201d for parkinsonism\u2019s treatment<\/a><\/td>5.3 Industrial biotechnologies: creation of producer strains<\/td>\n<\/tr>\n
Korenskaia A.<\/td>Bioinformatic assessment of factors affecting the correlation between protein abundance and elongation efficiency in prokaryotes<\/a><\/td>5.4 Modeling and computer analysis of microbiological systems and processes<\/td>\n<\/tr>\n
Kazantsev F.<\/td>Finding the ways for potential increasing of L-valine biosynthesis yield in C. glutamicum with mathematical modeling<\/a><\/td>5.4 Modeling and computer analysis of microbiological systems and processes<\/td>\n<\/tr>\n
Gentzbittel L.<\/td>Whole genome-based breeding in legumes<\/a><\/td>6.1 Genomics, genetics and system biology of plants<\/td>\n<\/tr>\n
Kiseleva A.<\/td>Dissection of candidate genes for grain texture in common wheat<\/a><\/td>6.1 Genomics, genetics and system biology of plants<\/td>\n<\/tr>\n
Kozlova L.<\/td> Methods to investigate the biomechanics of the plant cell wall<\/a><\/td>6.1 Genomics, genetics and system biology of plants<\/td>\n<\/tr>\n
Nizhnikov A.<\/td>Amyloid formation is a widespread phenomenon in land plant species<\/a><\/td>6.1 Genomics, genetics and system biology of plants<\/td>\n<\/tr>\n
Novikova P.<\/td>Adaptation to polyploidy in Siberian Arabidopsis lyrata<\/a><\/td>6.1 Genomics, genetics and system biology of plants<\/td>\n<\/tr>\n
Shmakov N.<\/td>Plant immunity genes of Solanum tuberosum L cultivars associ-ated with resistance to potato late blight<\/a><\/td>6.1 Genomics, genetics and system biology of plants<\/td>\n<\/tr>\n
Kharchenko V.<\/td>The real function of the gene TERMINAL FLOWER 1<\/a><\/td>6.2 Developmental biology of plants: computational and experimental approaches<\/td>\n<\/tr>\n
Kiryushkin A.<\/td>Does DEEPER ROOTING 1 (DRO1) gene of cucumber (Cucumis sativus L.) regulate a lateral root angle?<\/a><\/td>6.2 Developmental biology of plants: computational and experimental approaches<\/td>\n<\/tr>\n
Potsenovskaia E.<\/td>NF-Y genes in the somatic embryogenesis<\/a><\/td>6.2 Developmental biology of plants: computational and experimental approaches<\/td>\n<\/tr>\n
Sidorenko A.<\/td>Understanding the role of MAKR6 in Arabidopsis thaliana L. root development<\/a><\/td>6.2 Developmental biology of plants: computational and experimental approaches<\/td>\n<\/tr>\n
Tvorogova V.<\/td>Transcriptomic analysis for the optimization of transformation of legumes<\/a><\/td>6.2 Developmental biology of plants: computational and experimental approaches<\/td>\n<\/tr>\n
Xiuwei Cao<\/td>Condensation of STM empowers meristem activity and enhances salt tolerance<\/a><\/td>6.2 Developmental biology of plants: computational and experimental approaches<\/td>\n<\/tr>\n
Bashirzade A.<\/td>Combined treatment with autophagy inducers rapamycin and trehalose as an experimental therapy for Alzheimer\u2019s disease-like pathology in mice<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Kalueff A.<\/td>Neurogenomics of zebrafish<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Korolenko T.<\/td>Neurodegeneration and diabetes; positive effect of trehalose in behavior of db\/db mice, model of diabetes<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Mutovina A.<\/td>Different immune challenges alter hypothalamus microglia and astrocytes activity in the adult BTBR and C57Bl\/6 mice.<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Nazarova G.<\/td>Hereditary predisposition to seizures in response to handling and its relation to life expectancy in the water vole (Arvicola amphibius L.)<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Romashchenko \u0410.<\/td>Effect of divalent cations on the uptake of Mn3O4 nanoparticles by olfactory epithelial cells<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Salmina A.<\/td>Modern models of brain diseases for translational studies<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Savkin I.<\/td>Effects of the original synthetic ligand of benzodiazepine receptors in long-term alcoholized mice<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Sharapova M.<\/td>The role of manganese oxide nanoparticles in the formation of stress granules in the mouse olfactory system<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Smirnova K.<\/td>Effect of chronic unpredictable mild stress on stress resilience in Disc1-Q31L mice<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Stanova A.<\/td>The impact of temperature conditions of incubation on mouse embryonic development during in vitro fertilization<\/a><\/td>7.1 Genomics, genetics and system biology of animals<\/td>\n<\/tr>\n
Milyaeva P.<\/td>The role of the rhino gene in the transcriptional regulation of different piRNA clusters<\/a><\/td>7.2 Population and evolutionary genomics\/genetics of wild and domestic animals<\/td>\n<\/tr>\n
Trapezov O.<\/td>Regulatory effects of genes controlling behavior and painting shaping control. American mink (neovison vison) as a model<\/a><\/td>7.2 Population and evolutionary genomics\/genetics of wild and domestic animals<\/td>\n<\/tr>\n
Yudin N.<\/td>How does a harsh environment make wild and domestic animals evolve similarly?<\/a><\/td>7.2 Population and evolutionary genomics\/genetics of wild and domestic animals<\/td>\n<\/tr>\n
Bezdvornykh I.<\/td>Swaveform: a genome-wide survey of structural variation profiles<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Bratus A.<\/td>Mathematical model dynamics of pancreatic cancer with interaction of immune system. Approach by replicator quasispecies system.<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Chemeris D.<\/td>New solutions for medical genetics and biotechnologies from Maxim Medikal LLC<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Davydova A.<\/td>Hemoglobin-binding 2\u2032-F-modified RNA aptamers: structure studies and analytical application<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Fishman V.<\/td>Applications of next-generation sequencing for clinical diagnostics of monogenic diseases<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Korolenko T.<\/td>Autophagy inducer trehalose positive effect in db\/db mice, genetic model of diabetes<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Kovner A.<\/td>A new approach to stimulating the wound healing based on Opisthorchis felineus proteins<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Kozhevnikova O.<\/td>Pharmacogenetic influence of complement genes genotypes on the response to anti-VEGF treatment for age-related macular degeneration in a Russian population<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Krasner K.<\/td>Relex Smile lenticules as a source of obtaining stromal corneal cells<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Letyagin A.<\/td>Artificial intelligence (AI) of 3D MRI images for neurooncology<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Nebrat V.<\/td>Human water model: interstitium and meridians of traditional Chinese medicine<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Permyakova E.<\/td>Curdlan\/Chitosan\/Ag NPs Foams for healing chronic wounds<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Popov D.<\/td>Role of HSP70 proteins in regulation of mitochondrial protein content in skeletal muscle<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Saik O.<\/td>Uncovering the genes linking glucose variability with endothelial dysfunction in diabetes by the analysis of gene networks<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Shatunova E.<\/td>Dkk-1 level detection in ankylosing spondylitis by the aptamer-based colorimetric assay<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Shelenkov A.<\/td>Computational pipeline and database for the epidemiological typing and antimicrobial resistance profiling of important bacterial pathogens<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Sitnikova N.<\/td>Ag modification of PLC-COOH nanofibers provides mesenchymal cells proliferation<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Turubanova V.<\/td>Vaccination with dendritic cells pulsed with glioma killed by photodynamic therapy induces efficient antitumor immunity<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Vlasenkova R.<\/td>Construction of comprehensive amino acid networks from Molecular Dynamics trajectories and tumor mutational profile of human sodium transporter NaPi2b<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Vorobyeva M.<\/td>Oligonucleotide aptamers for diagnosis and treatment of human diseases<\/a><\/td>8. Biomedicine, bioinformatics and systems computational biology<\/td>\n<\/tr>\n
Arefieva N.<\/td>Detection of recombination events in coronavirus genomes from the subgenus sarbecovirus<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Basu A.<\/td>Epigenetics behind SARS COV2<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Bocharov G.<\/td>Mathematical modelling of antiviral immune responses to SARS-CoV-2 infection<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Das R.<\/td>Genomic variation underlies the severity of COVID-19 clinical manifestation<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Djordjevic M.<\/td>Combining machine learning and non-linear dynamics modeling to understand COVID-19 risk factors<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Efimov K.<\/td>New features of the PCA-Seq method in time series analysis (on the example of COVID-19)<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Gorelov S.<\/td>Finding possible inhibitors for SARS-CoV-2 proteins using virtual ligand screening<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Ilic B.<\/td>Analytical and numerical study of infection progression under social distancing measures<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Kaminskiy G.<\/td>Behavior changes of epidemic control in condition of sufficient and limited resources<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Kisselevskaya-Babinina V.<\/td>Markov model of hospitalized patients with COVID-19<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Kolokoltsov V.<\/td>Fighting ticks with functional-analytic guns<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Kornienko E.<\/td>The potential usability of Oxford Nanopore Technology for revealing of SARS-CoV-2 dual infection and intra-host viral variability in clinical samples<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Krivorotko O.<\/td>Mathematical modeling and identifiability aspects in epidemiology<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Miroshnichenko M.<\/td>Mathematical modeling of SARS-CoV-2 infection process and virus spreading in the human body considering B and T cell-mediated immune responses<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Nenad Mitic<\/td>Large scale clustering in structural and evolutionary analysis of SARS-CoV-2 proteins<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Netesov S.<\/td>Coronavirus SARS-CoV2 preliminary results of the pandemic<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Novikov K.<\/td>Coupled agent-based model of COVID-19 and major depressive disorder spread in Moscow<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Petrakova V.<\/td>Mathematical modeling of the dynamics of incomes of the population under epidemic process<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Rodic A.<\/td>Modeling the COVID-19 transmission dynamics and identifying meteorological and sociodemographic predictors<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Sannikova T.<\/td>Seeking the threshold for herd immunity in the synthetic population of a medium-sized city<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Taranik A.<\/td>Forecast of the development of the COVID-19 epidemic situation in Moscow in 2022-2023<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Trusov N.<\/td>Consumer loan demand modeling of households in Russia under sanctions<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Vlad A.<\/td>Transmission of acute respiratory infections in a city: agent-based approach<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Zvonareva T.<\/td>Mathematical modeling of information diffusion in Twitter<\/a><\/td>9. Mathematics, bioinformatics and systems computational biology of COVID-19<\/td>\n<\/tr>\n
Eremin D.<\/td>Effects of central administration of Cerebral dopamine neurotrophic factor (CDNF) on the behavior and serotonin system in the mouse brain<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Kaminskaya Ya.<\/td>Hippocampal\u0412 overexpression of cerebral dopamine neurotrophic factor (CDNF)\u0412 affected the behavior of mice with genetically-defined depressive-like behavior<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Kazantseva A.<\/td>The use of genetic risk score approach to predict higher depression risk in young adults<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Klemeshova D.<\/td>Analysis of behavioral and EEG responses given the performing tasks to control attention and behavior in children with emotional instability<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Ozgoren M.<\/td>Brain functioning across regions and dimensions lessons learned from dic<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Ratushnyak A.<\/td>The emergence and evolution of living systems compensating for entropy processes<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Shtern E.<\/td>P.Y. Halperin\u2019s Activity Theory and Language Consciousness Theory: Results of EEG-Based Research in the Perspective of ICT-assisted Foreign Language Learning<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Smirnova L.<\/td>IgG-Dependent dismutation of Superoxide and DPPH radical in patients with schizophrenia<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Valdes-Sosa<\/td>Probing developmental disorders with multivariate quantitative EEG analysis<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Chernigovskaya T.<\/td>Homo semiotocus: Neuroscience and Other Logics<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Anohin K.<\/td>\u041f\u0440\u0438\u0440\u043e\u0434\u0430 \u043a\u043e\u0433\u043d\u0438\u0442\u0438\u0432\u043d\u043e\u0439 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Kireev M.<\/td>\u041c\u043e\u0437\u0433\u043e\u0432\u044b\u0435 \u043c\u0435\u0445\u0430\u043d\u0438\u0437\u043c\u044b \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u043c\u043d\u043e\u0433\u043e\u0437\u043d\u0430\u0447\u043d\u043e\u0439 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Smirnova L.<\/td>IgG-Dependent dismutation of Superoxide and DPPH radical in patients with schizophrenia<\/a><\/td>10. Cognitive sciences, neurogenetics, neuroinformatics and systems computational biology<\/td>\n<\/tr>\n
Alemasova E.<\/td>Role of PAR and RNA in biomolecular condensate formation<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Bogachev S.<\/td>The novel radioprotective agent <\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Diatlova E.<\/td>Base excision repair in non-canonical DNA structures<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Dyrkheeva N.<\/td>TOP1, TDP1, and PARP1 inhibition: coupling and association<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Endutkin A.<\/td>Bioorthogonality in the light of cell defense mechanisms: interaction of non-natural nucleic acids with the base excision dna repair system<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Kubareva E.<\/td>G-quadruplex formed by the promoter region of the hTERT gene:
\nstructure-driven effects on DNA mismatch repair functions<\/a><\/td>		11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Kulms D.<\/td>Focal adhesion kinase plays a dual role in TRAIL resistance and metastatic outgrowth of malignant melanoma<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Kutuzov M.<\/td>PARP2 and BER in the nucleosomal context<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Lavrik O.<\/td>Regulation of PARP1 activity by its protein partners<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Maluchenko N.<\/td>Nucleosome reorganization by PARP-1<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Zharkov D.<\/td>Structure and function evolution in DNA repair<\/a><\/td>11. Systems biology and bioinformatics of DNA repair processes and programmed cell death<\/td>\n<\/tr>\n
Alekseev A.<\/td>Validation of metabolic aging trends on multiple databases<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Anisimov V.<\/td>Multi-stage model of aging and carcinogenesis<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Evgen\u2019ev M.<\/td>Hsp70 and donors of H2S in aging-associated diseases and inflammation<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Khalyavkin A.<\/td>Aging is a sequential multisystem syndrome, preventable and reversible under certain conditions<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Khokhlov A.<\/td>Fighting Alzheimer\u2019s disease: is there a chance to conquer?<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Kolodkin A.<\/td>ROS networks: designs, aging, Parkinson\u2019s disease and preci-sion therapies<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Kriukov D.<\/td>Longevity And Rejuvenation Effects Of Cell Reprogramming Are Decoupled From The Loss Of Somatic Identity<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Morgunova G.<\/td>Relationship between basal metabolic rate, muscle strength and aging<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Rudnitskaya E.<\/td>Alteration of hippocampal glial support during early postnatal development as a possible premise of Alzheimer\u2019s disease<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Salmina A.<\/td>Aberrant neuroplasticity in aging and neurodegeneration associated with deregulation of neurogenesis and angiogenesis<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Rybina O.<\/td>Transcription regulation in aging and lifespan control<\/a><\/td>12. Systems biology of aging: experimental and computational approaches<\/td>\n<\/tr>\n
Antezana M.<\/td>A novel, computationally tractable algorithm flags in big matrices every column associated in any way with others or a dependent variable, with much higher power when columns are linked like mutations in chromosomes<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Brodt K.<\/td>Deep learning for the development of an OCR for old Tibetan books<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Gam A.<\/td>Implementation of a spanning trees sampling algorithm to detect 4-motifs<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Genaev M.<\/td>Classification of fruit flies by gender in images based on the YOLOv4-tiny neural network using mobile devices<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Golubyatnikov V.<\/td>Mathematical and numerical modelling of the circadian oscillator<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Golubyatnikov V.<\/td>On uniqueness and stability of a cycle of one Elowitz-Leibler type dynamical system<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Karpenko D.<\/td>Multidimensional analysis, dimension reduction, categorization with statistical approach \u2013 stability and reproducibility<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Karpenko D.<\/td>Recursive matrix algorithm for calculating differential expressions<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Lakhno V.<\/td>Bioinformatics and nanobioelectronics. Informatics based on biocomputer technologies<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Meshcheryakov G.<\/td>Beta negative binomial mixture model facilitates identification of allele-specific gene regulation in high-throughput sequencing data<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Palyanov A.<\/td>Towards artificial minds through computer simulation of natural ones, from simple to more complex<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Titov A.<\/td>Space-time correlation analysis in bio-macro-molecules, based on molecular dynamic trajectory data<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Palyanov A.<\/td>Towards artificial minds through computer simulation of natural ones, from simple to more complex<\/a><\/td>13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing<\/td>\n<\/tr>\n
Danilenko V.<\/td>Study of human and animal microbiome as genetic and pharmacological resources for the development of innovative biotechnologies for medicine, animal husbandry and agro-industrial complex.<\/a><\/td>Plenary session<\/td>\n<\/tr>\n
Kulakovskiy I.<\/td>Interpreting non-coding genome variation with DNA sequence motifs<\/a><\/td>Plenary session<\/td>\n<\/tr>\n
Sulgina T.<\/td>3D-Tomography without Tomographic Equipment. Bioluminescence and Fluorescence In Vivo Imaging System Newton 7.0 (Vilber)<\/a><\/td>Plenary session<\/td>\n<\/tr>\n
Popov V.<\/td>From 3D protein structure to biological function
\n<\/a><\/td>		Plenary session<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/pages\/18040"}],"collection":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/comments?post=18040"}],"version-history":[{"count":5,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/pages\/18040\/revisions"}],"predecessor-version":[{"id":18149,"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/pages\/18040\/revisions\/18149"}],"wp:attachment":[{"href":"https:\/\/bgrssb.icgbio.ru\/2022\/ru\/wp-json\/wp\/v2\/media?parent=18040"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}