{"id":3974,"date":"2024-08-30T10:39:48","date_gmt":"2024-08-30T07:39:48","guid":{"rendered":"https:\/\/bgrssb.icgbio.ru\/2024\/ru\/?page_id=3974"},"modified":"2024-09-19T07:14:43","modified_gmt":"2024-09-19T04:14:43","slug":"video_reports","status":"publish","type":"page","link":"https:\/\/bgrssb.icgbio.ru\/2024\/video_reports\/","title":{"rendered":"Video of reports"},"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\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
Ivan Kulakovsky<\/td>Do we understand the grammar of nucleotide sequences controlling eukaryotic gene expression? From pattern matching in strings to AI-assisted rational design<\/a><\/td>Plenary lectures, Opening of the conference<\/td>\n<\/tr>\n
Ivan Gushchin<\/td>X-ray crystallography in the era of high-quality predictions<\/a><\/td>Plenary lectures, Opening of the conference<\/td>\n<\/tr>\n
Yan Zubavichus<\/td>Synchrotron radiation facility SKIF: structural biology-related instruments and research plans<\/a><\/td>Plenary lectures, Opening of the conference<\/td>\n<\/tr>\n
Chen Ming<\/td>Big data-based studies on neurodegenerative-related interactome, aging and longevity<\/a><\/td>Plenary lectures, Opening of the conference<\/td>\n<\/tr>\n
Gennady Bocharov<\/td>System immunology: multiphysics modelling approach<\/a><\/td>Plenary lectures, Opening of the conference<\/td>\n<\/tr>\n
Elena Ilina<\/td>Systems approach in research of human microbiome in the context of human health<\/a><\/td>Plenary lectures, Opening of the conference<\/td>\n<\/tr>\n
Inna Lavrik<\/td>Experimental-computational approaches to the analysis of programmed cell death<\/a><\/td>Plenary lectures, Opening of the conference<\/td>\n<\/tr>\n
Pedro Antonio Vald\u00e9s-Sosa<\/td>The Riemannian nonlinear geometry of electroencephalogam development across the lifespan<\/a><\/td>Plenary lectures, Closing of the conference<\/td>\n<\/tr>\n
Evgeny Denisov<\/td>Omics technologies at the single cell and spatial resolution levels: opportunities and prospects<\/a><\/td>Plenary lectures, Closing of the conference<\/td>\n<\/tr>\n
Vorontsov Konstantin<\/td>Evolution of ideas in artificial intelligence and their relationship to the challenges of biomedicine and bioinformatics<\/a><\/td>Plenary lectures, Closing of the conference<\/td>\n<\/tr>\n
Pasyukova Elena Genrikhovna<\/td>\u041f\u0440\u043e\u0442\u0435\u0438\u043d\u043a\u0438\u043d\u0430\u0437\u044b \u0438 \u0442\u0440\u0430\u043d\u0441\u043a\u0440\u0438\u043f\u0446\u0438\u043e\u043d\u043d\u044b\u0435 \u0444\u0430\u043a\u0442\u043e\u0440\u044b \u0432 \u0441\u0438\u0441\u0442\u0435\u043c\u043d\u043e\u0439 \u0440\u0435\u0433\u0443\u043b\u044f\u0446\u0438\u0438 \u043f\u0440\u043e\u0434\u043e\u043b\u0436\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u0436\u0438\u0437\u043d\u0438<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Veselkina Ekaterina<\/td>The expression level of GSK3 in specific groups of dopaminergic neurons influences the lifespan and behavior of Drosophila melanogaster<\/i><\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Morgunova Galina<\/td>Investigation of the effect of the 7-hydroxycoumarin derivative UB3-C10 on chronological aging of human myoblasts MB135 in vitro<\/i><\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Golubenko Maria<\/td>Mitochondrial DNA variants combinations as a risk factor for developing of arrhythmia<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Khokhlov Alexander<\/td>Antioxidants: good, bad, or ineffective in terms of aging and lifespan? It depends.<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Proshkina Ekaterina<\/td>Genetic and pharmacological piwi suppression modulates lifespan and radioresistance of Drosophila melanogaster<\/i><\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Symonenko Alexander<\/td>Changes in the expression of the Stc transcription factor in the nervous system and muscle tissue increase the healthspan of Drosophila<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Moskalev Alexey<\/td>Potential geroprotectors - from laboratory to clinic<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Kurochkina Nadia<\/td>Knockout of Hsp70<\/i> genes causes changes in the transcriptome of leg skeletal muscles and locomotion speed in D. melanogaster<\/i> comparable to age-related changes<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Matveeva Kseniia<\/td>Transcriptional Signatures and Age-Related Changes in CD8+HLA-DR+ Regulatory T Cells<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Snytnikova Olga<\/td>Quantitative metabolomic profile of blood serum and brain of OXYS rats \u2013 a model of Alzheimer\u2019s disease<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Stepanichev Mikhail<\/td>Changes in behavior and the stress-responsive system in the aging SHR and WKY rats after prolonged individual housing<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Orlova Mira<\/td>Effects of age and long-term disuse on proteome of human skeletal muscle<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Stefanova Natalia<\/td>Insufficient neuronal support by glial cells as a predictor and driver of Alzheimer\u2019s diseaselike pathology in OXYS rats<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Kholdina Daria<\/td>From Genes to Gears: Exploring the Mechanics of Aging and Longevity Through Transcriptomic Clocks and Network Analysis<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Kriukov Dmitrii<\/td>Epistemic uncertainty hinders reliable prediction of rejuvenation with aging clocks<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Efimov Evgeniy<\/td>Developing a standardized methodology to validate epigenetic aging clocks<\/a><\/td>13 Genetics and systems biology of aging<\/td>\n<\/tr>\n
Vityaev Evgenii<\/td>The implementation in the Task-driven approach to Artificial Intelligence the P.K.Anokhin's idea of generalizing the Theory of Functional Systems to other fields of knowledge<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Nechesov Andrey<\/td>Programming methodology for trusted artificial intelligence<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Ivanisenko Timofey<\/td>Enhancing biomedical knowledge discovery through hybrid text-mining and graph neural network approaches in ANDSystem<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Palyanov Andrey<\/td>Millions of SARS-CoV-2 genomes in the RAM of a regular PC: fast and efficient analysis of evolutionary changes<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Perik Zavodskii Roman<\/td>TCRscape \u2013 a tool for simultaneous multimodal gene expression analysis of single Tcells and their clonotypes<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Firsov Artemiy<\/td>miRNA science as an intellectual epidemy<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Meshcheryakov Georgy<\/td>Toward improved calling of allele-specific events in highthroughput sequencing data with a mixture of compound Dirichlet negative multinomial distributions<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Kondratyev Dmitry Alexandrovich<\/td>Formal verification of neural networks<\/a><\/td>12.3 Systems theory, big biological data analysis, ontologies and artificial intelligence<\/td>\n<\/tr>\n
Loginov Konstantin Konstantinovich<\/td>Numerical study of the initial stage of spread of HIV-1 infection in a lymphatic node based on a stochastic model and the Monte Carlo method<\/a><\/td>12.2 Mathematical immunology<\/td>\n<\/tr>\n
Bocharov Gennady<\/td>Frontier modelling challenges in mathematical immunology<\/a><\/td>12.2 Mathematical immunology<\/td>\n<\/tr>\n
Khristichenko Michael<\/td>Computation and analysis of stationary solutions of the COVID-19 infection dynamics mode<\/a><\/td>12.2 Mathematical immunology<\/td>\n<\/tr>\n
Panova Anastasiia<\/td>Modeling of infection in a local atmosphere with a random concentration of SARS-COV-2 virus<\/a><\/td>12.2 Mathematical immunology<\/td>\n<\/tr>\n
Karpenko Dmitriy<\/td>Complexity of immune suppression underlying immune privileges in stem system<\/a><\/td>12.2 Mathematical immunology<\/td>\n<\/tr>\n
Fedorova Valentina<\/td>Mathematical modeling of the promising composition of the next generation safe epitope vaccine against porcine salmonellosis<\/a><\/td>12.2 Mathematical immunology<\/td>\n<\/tr>\n
Kolpakov Fedor<\/td>The virtual cell<\/a><\/td>12.1 Mathematical and simulation modeling, digital twins<\/td>\n<\/tr>\n
Kondrakhin Pavel<\/td>Multilevel mathematical model of epileptic seizures<\/a><\/td>12.1 Mathematical and simulation modeling, digital twins<\/td>\n<\/tr>\n
Golubyatnikov Vladimir<\/td>Non-uniqueness of cycles and hidden attractors in multistage gene networks models<\/a><\/td>12.1 Mathematical and simulation modeling, digital twins<\/td>\n<\/tr>\n
Rakshun Yakov Valerievich<\/td>\u0418\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0443\u0430\u043b\u044c\u043d\u044b\u0435 \u0446\u0438\u0444\u0440\u043e\u0432\u044b\u0435 \u0434\u0432\u043e\u0439\u043d\u0438\u043a\u0438 \u0441 \u0441\u0438\u0441\u0442\u0435\u043c\u0430\u043c\u0438 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u043a\u0438 \u043f\u0440\u0438\u043d\u044f\u0442\u0438\u044f \u0440\u0435\u0448\u0435\u043d\u0438\u0439 \u044d\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442\u0430\u043b\u044c\u043d\u043e\u0439 \u0441\u0442\u0430\u043d\u0446\u0438\u0438 1-1 \u00ab\u041c\u0438\u043a\u0440\u043e\u0444\u043e\u043a\u0443\u0441\u00bb \u0421\u041a\u0418\u0424<\/a><\/td>12.1 Mathematical and simulation modeling, digital twins<\/td>\n<\/tr>\n
Marchenko Mikhail<\/td>\u0426\u0438\u0444\u0440\u043e\u0432\u044b\u0435 \u0434\u0432\u043e\u0439\u043d\u0438\u043a\u0438 \u0442\u0435\u0445\u043d\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0438 \u043f\u0440\u0438\u0440\u043e\u0434\u043d\u044b\u0445 \u0441\u0438\u0441\u0442\u0435\u043c, \u0438 \u0432\u043e\u043f\u0440\u043e\u0441\u044b \u0438\u0441\u043a\u0443\u0441\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0438\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0430<\/a><\/td>12.1 Mathematical and simulation modeling, digital twins<\/td>\n<\/tr>\n
Petoukhov Sergey Valentinovich<\/td>\u0421\u0432\u044f\u0437\u044c \u0433\u0435\u043d\u0435\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0441 \u0446\u0438\u043a\u043b\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u043a\u043e\u0434\u0430\u043c\u0438 \u0413\u0440\u0435\u044f. \u041f\u0440\u043e\u0431\u043b\u0435\u043c\u0430 \u043d\u0430\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u044f \u0431\u0438\u043e\u0446\u0438\u043a\u043b\u043e\u0432<\/a><\/td>12.1 Mathematical and simulation modeling, digital twins<\/td>\n<\/tr>\n
Daniil Parshin<\/td>Hemodynamics of aneurysms: modeling and experiment<\/a><\/td>12.1 Mathematical and simulation modeling, digital twins<\/td>\n<\/tr>\n
Kolpakov Fedor Anatolevich<\/td>Computer modelling of appoptosis<\/a><\/td>11.3 Apoptosis and other fundamental cellular processes that regulate cell fate<\/td>\n<\/tr>\n
Babushkina Nadezhda<\/td>\u041c\u0435\u0442\u0438\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0440\u0435\u0433\u0443\u043b\u044f\u0442\u043e\u0440\u043d\u044b\u0445 \u0440\u0435\u0433\u0438\u043e\u043d\u043e\u0432 \u0430\u043f\u043e\u043f\u0442\u043e\u0437-a\u0441\u0441\u043e\u0446\u0438\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0433\u0435\u043d\u043e\u0432 \u043f\u0440\u0438 \u0434\u0438\u0441\u0442\u0440\u043e\u043f\u0438\u0438<\/a><\/td>11.3 Apoptosis and other fundamental cellular processes that regulate cell fate<\/td>\n<\/tr>\n
Tarasova Irina<\/td>Functional cross-talks between transcription, alternative splicing, translation and novel posttranslational modifications in Alzheimer disease: fill missings using proteomics<\/a><\/td>11.3 Apoptosis and other fundamental cellular processes that regulate cell fate<\/td>\n<\/tr>\n
Sokolova Olesya<\/td>\u0412\u044b\u044f\u0432\u043b\u0435\u043d\u0438\u0435 \u043c\u0438\u0448\u0435\u043d\u0435\u0439 \u0442\u0440\u0430\u043d\u0441\u043a\u0440\u0438\u043f\u0446\u0438\u043e\u043d\u043d\u043e\u0439 \u0440\u0435\u0433\u0443\u043b\u044f\u0446\u0438\u0438 \u0438\u043d\u0441\u0443\u043b\u044f\u0442\u043e\u0440\u043d\u043e\u0433\u043e \u0431\u0435\u043b\u043a\u0430 BEAF32 \u0438 \u0438\u0437\u0443\u0447\u0435\u043d\u0438\u0435 \u0435\u0433\u043e \u0440\u043e\u043b\u0438 \u0432 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0430\u043d\u0438\u0438 pi\u0420\u041d\u041a-\u043a\u043b\u0430\u0441\u0442\u0435\u0440\u043e\u0432 \u0432 \u0433\u0435\u0440\u043c\u0438\u043d\u0430\u043b\u044c\u043d\u044b\u0445 \u0442\u043a\u0430\u043d\u044f\u0445 Drosophila melanogaster<\/i><\/a><\/td>11.3 Apoptosis and other fundamental cellular processes that regulate cell fate<\/td>\n<\/tr>\n
Graifer Dmitri<\/td>Hotspots in ribosomal proteins \u2013 determinants of the translation machinery and beyond<\/a><\/td>11.2 Transcription, splicing, translation<\/td>\n<\/tr>\n
Alkalaeva Elena<\/td>Regulation of eukaryotic translation termination by initiation complex<\/a><\/td>11.2 Transcription, splicing, translation<\/td>\n<\/tr>\n
Alkalaeva Elena<\/td>The last sense codon and the poly(A) tail of mRNA regulate the termination of eukaryotic translation<\/a><\/td>11.2 Transcription, splicing, translation<\/td>\n<\/tr>\n
Shepelev Nikita<\/td>Search for upstream open reading frames that are essential for viability of human cell lines<\/a><\/td>11.2 Transcription, splicing, translation<\/td>\n<\/tr>\n
Saparbaev Murat<\/td>Intra-strand DNA symmetry provides insight into evolution of complex life form<\/a><\/td>11.1 DNA replication and repair<\/td>\n<\/tr>\n
Zharkov Dmitry<\/td>Order and disorder in base excision DNA repair<\/a><\/td>11.1 DNA replication and repair<\/td>\n<\/tr>\n
Varizhuk Anna<\/td>G-quadruplexes at superenhancers and CTCF clusters help shape topologically associating domains \/ replication domains<\/a><\/td>11.1 DNA replication and repair<\/td>\n<\/tr>\n
Stolyarenko Anastasia<\/td>The catalytic activity of human REV1 on undamaged and damaged DNA<\/a><\/td>11.1 DNA replication and repair<\/td>\n<\/tr>\n
Backman Artemy<\/td>Kinetic features of protein-DNA and protein-protein interactions of APE1 and Pol\u03b2 during the base excision repair<\/a><\/td>11.1 DNA replication and repair<\/td>\n<\/tr>\n
Yakovlev Alexandr<\/td>The ability of polymerases of different families to process substrates containing clickchemical modifications of the sugar-phosphate backbone<\/a><\/td>11.1 DNA replication and repair<\/td>\n<\/tr>\n
Irina Tarasova<\/td>Protocol testing and electrophysiological changes associated with multitasking cognitive training in virtual reality<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Anna Andreevna Arinicheva<\/td>Diagnosis of Cognitive Distortions in Public, Group, and Personal Text Communications<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Kseniya Zorina<\/td>EEG reactions in healthy children and children with behavioral control disorders during performing tasks in the stop-signal paradigm<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Vera Alexeevna Semiletova<\/td>EEG correlates of the influence of speleoclimate on the brain activity of an adult healthy person<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Smirnova Liudmila<\/td>Using the MaxQuant tool to search for biomarkers of bipolar disorder<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Shaliapina Anna<\/td>Cognitive and personality siblings\u2019 features and oral speech<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Filimonov Viacheslav<\/td>Remarks on the draft of the fundamental theory of mind<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Abramova Victoria<\/td>Dynamic Changes in Neurovascular Connectivity in Patients with stroke: A Study of Resting-State fMRI and Cerebral Perfusion<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Andrey Bocharov<\/td>Associations of self-focus attention to oscillatory dynamics of self- recognition in morphed images<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Dmitry Lebedkin<\/td>Perception of self- and otherreferential sentences with varying emotional content: a neurolinguistic study<\/a><\/td>10 General problems in the study of cognitive processes; models of cognitive activity<\/td>\n<\/tr>\n
Letyagin Andrey<\/td>Interstitium: biofeedback and drainage transport of fluids, crystalloids, biopolymers and cells<\/a><\/td>9.6 Interstitial space and long extravascular drainage\/transport pathways<\/td>\n<\/tr>\n
Bgatova Nataliya<\/td>General principles of structure and ultrastructural differences in the interstitial pathways of tissue fluid movement<\/a><\/td>9.6 Interstitial space and long extravascular drainage\/transport pathways<\/td>\n<\/tr>\n
Nebrat Vladimir<\/td>Photobiomodulation and interstitium in medicine: new challenges and prospects<\/a><\/td>9.6 Interstitial space and long extravascular drainage\/transport pathways<\/td>\n<\/tr>\n
Trashkeev Sergey<\/td>Exploring the potential of liquid crystal physics in biology<\/a><\/td>9.6 Interstitial space and long extravascular drainage\/transport pathways<\/td>\n<\/tr>\n
Ushakov Andrey<\/td>Pathogenesis of thyroid stromal swelling<\/a><\/td>9.6 Interstitial space and long extravascular drainage\/transport pathways<\/td>\n<\/tr>\n
Taskaeva Iuliia<\/td>Features of extracellular matrix remodeling in human uveal melanoma<\/a><\/td>9.6 Interstitial space and long extravascular drainage\/transport pathways<\/td>\n<\/tr>\n
Prokudina Ekaterina<\/td>\u0424\u0438\u0431\u0440\u043e\u0438\u043d \u0448\u0451\u043b\u043a\u0430 \u2013 \u043e\u0441\u043d\u043e\u0432\u0430 \u0442\u043a\u0430\u043d\u0435\u0438\u043d\u0436\u0435\u043d\u0435\u0440\u043d\u043e\u0439 \u0437\u0430\u043f\u043b\u0430\u0442\u044b \u0434\u043b\u044f \u0430\u0440\u0442\u0435\u0440\u0438\u0430\u043b\u044c\u043d\u043e\u0439 \u0440\u0435\u043a\u043e\u043d\u0441\u0442\u0440\u0443\u043a\u0446\u0438\u0438<\/a><\/td>9.5 Tissue engineering<\/td>\n<\/tr>\n
Sorokina Irina<\/td>Neuromodulators of the azaadamantane type: prospects for use in neurodegenerative pathologies<\/a><\/td>9.4 Innovative pharmacology<\/td>\n<\/tr>\n
Dmitrii Baev<\/td>Molecular modeling of the mechanism of antiviral action of new conjugates of 1,7,7-trimethylbicyclo[2.2.1]heptane and saturated N-heterocycles linked by a 1,2,3-triazole linker against the Marburg virus<\/a><\/td>9.4 Innovative pharmacology<\/td>\n<\/tr>\n
Sergey Borisov<\/td>Dihydrobetulonic acid derivatives as potential dual PP\u0410R-\u03b1 and PP\u0410R-\u03b3 agonists<\/a><\/td>9.4 Innovative pharmacology<\/td>\n<\/tr>\n
Zakharova Irina<\/td>Cellular models of familial hypercholesterolaemia: new horizons in the fight against atherosclerosis<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Malakhova Anastasia<\/td>\u041a\u043b\u0435\u0442\u043e\u0447\u043d\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438 \u0431\u043e\u043b\u0435\u0437\u043d\u0438 \u041f\u0430\u0440\u043a\u0438\u043d\u0441\u043e\u043d\u0430 \u0438 \u0431\u043e\u043b\u0435\u0437\u043d\u0438 \u0413\u0435\u043d\u0442\u0438\u043d\u0433\u0442\u043e\u043d\u0430 \u0434\u043b\u044f \u0438\u0437\u0443\u0447\u0435\u043d\u0438\u044f \u043f\u0430\u0442\u043e\u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0432 \u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u0430\u0445<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Makeeva Vladlena<\/td>Effect of PARP1 inhibitor on expression of genes associated with Huntington's disease in differentiated iPSC derivatives<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Nadtochiy Julia<\/td>Transgenic cell lines to study the interaction of tau protein with microtubules and to analyze mitochondrial dysfunction caused by the c.2013T>G (p.N279K) genetic variant in the MAPT<\/i> gene<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Chvileva Anastasia<\/td>Investigating the effect of HAR deletion located in the CNTN6<\/i> gene on early stages of human neurogenesis on the cerebral organoids mode<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Karagyaur Maxim<\/td>Identification and establishment of functional significance of single nucleotide missense variants in brain morphogeni\u0441 genes in the context of psychiatric and cognitive disorders<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Smirnikhina Svetlana A<\/td>Correction of pathogenic variants of the CFTR gene for the development of treatments for cystic fibrosis<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Levchenko Olga<\/td>\u041f\u0435\u0440\u043c\u0430\u043d\u0435\u043d\u0442\u043d\u044b\u0439 \u044d\u043a\u0437\u043e\u043d-\u0441\u043a\u0438\u043f\u043f\u0438\u043d\u0433 \u043f\u0443\u0442\u0435\u043c \u0440\u0430\u0437\u0440\u0443\u0448\u0435\u043d\u0438\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441\u043f\u043b\u0430\u0439\u0441\u0438\u043d\u0433\u0430 \u044d\u043a\u0437\u043e\u043d\u043e\u0432 43-55 \u0433\u0435\u043d\u0430 DMD \u043c\u0435\u0442\u043e\u0434\u043e\u043c CRISPR\/Cas9<\/a><\/td>9.3 Gene and genome editing in modeling human pathological disease processes<\/td>\n<\/tr>\n
Vorobyeva Mariya<\/td>Aptamers to inflammationassociated proteins and their prospects for biomedical applications<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Frank Ludmila<\/td>Highly sensitive microassay based on artificial luciferase NLuc for the diagnosis of socially significant diseases<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Karpova Nataliia Sergeevna<\/td>Identification of shared and distinct genetic variants associated with type 2 diabetes mellitus and gestational diabetes mellitus<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Agareva Margarita<\/td>Semaglutide enhances the thermogenesis of beige adipocytes derived from mesenchymal stem cells of subcutaneous adipose tissue of patients with type 2 diabetes mellitus<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Naumenko Mariia<\/td>Shedding light on cell proliferation: cell culture monitoring using light scattering<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Kiseleva Diana<\/td>Proatherogenic potential of oxidative modifications in LDL<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Ziablitskaia Evgeniia<\/td>Study of mutations in the tissue of the main types of thyroid tumors in primary and metastatic foci<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Ziablitskaia Evgeniia<\/td>Predictive significance of polymorphisms of the VEGFA, eNOS, IFNL3, IL-6, TP53, ITGA2 genes in the diagnosis of colorectal cancer<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Lykov Alexander<\/td>Biological consequences of cyanobacteria and microalgae<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Ponomarenko Andrei Viktorovich<\/td>Evaluating the Impact of Omega-3 Fatty Acid (SolowaysTM) Supplementation on Lipid Profiles in Adults with PPARG Polymorphisms: A Randomized, Double-Blind, Placebo-Controlled Trial<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Dmitrienko Elena<\/td>Phosphorylguanidine derivatives of oligonucleotide as perspective tools for development of highly sensitive systems for nucleic acids diagnostics<\/a><\/td>9.2 Molecular Pathology, Diagnostics, and Therapeutics<\/td>\n<\/tr>\n
Shirinsky Ivan<\/td>The link between obesity and osteoarthritis: is it mechanical stress or something else?<\/a><\/td>9.1 Gene expression and human diseases<\/td>\n<\/tr>\n
Gorbacheva Anna<\/td>Splicing isoforms of SIRT1 in the liver of patients with metabolic syndrome - expectation\/reality<\/a><\/td>9.1 Gene expression and human diseases<\/td>\n<\/tr>\n
Arakelyan Arsen<\/td>Assigning transcriptomic subtypes to CML\/CLL samples using nanopore RNAsequencing and self-organizing maps<\/a><\/td>9.1 Gene expression and human diseases<\/td>\n<\/tr>\n
Michurina Svetlana<\/td>Overexpression of creatine kinase B and glycerol kinase activates thermogenic futile cycles in adipocytes<\/a><\/td>9.1 Gene expression and human diseases<\/td>\n<\/tr>\n
Kozhevnikova Oyuna<\/td>microRNA and response to antiVEGF therapy of neovascular age-related macular degeneration in a Russian cohort: experi-ence of use as a tool for personalized medicine<\/a><\/td>9.1 Gene expression and human diseases<\/td>\n<\/tr>\n
Bairqdar Ahmad<\/td>Differential expression of various LncRNAs and microRNAs in abdominally obese and nonobese individuals<\/a><\/td>9.1 Gene expression and human diseases<\/td>\n<\/tr>\n
Fedorenko Alisa<\/td>Knockout or Deletion of the UBE2A Gene Leads to Disruption of the Rho\/ROCK Signaling Pathway and Impaired Migra-tion of Neural Cells Differentiated from iPSCs<\/a><\/td>9.1 Gene expression and human diseases<\/td>\n<\/tr>\n
Sorokin Anatoly<\/td>Modelling of bacterial metabolism and metabolic interspecies interactions in reach media<\/a><\/td>8.4 Modeling and computational analysis of microbiological systems and processes<\/td>\n<\/tr>\n
Rodic Andjela<\/td>Insights into the natural activation mechanism of the CRISPR-Cas immune system in Escherichia coli<\/i> from a computational modeling analysis<\/a><\/td>8.4 Modeling and computational analysis of microbiological systems and processes<\/td>\n<\/tr>\n
Kazantsev Fedor<\/td>A software package to assess the metabolic potential of mutant strains of the Corynebacterium glutamicum<\/i><\/a><\/td>8.4 Modeling and computational analysis of microbiological systems and processes<\/td>\n<\/tr>\n
Popova Anastasiya<\/td>Search and description of diversity, evolution of restriction-modification systems in hyperthermophilic bacteria and archaea<\/a><\/td>8.4 Modeling and computational analysis of microbiological systems and processes<\/td>\n<\/tr>\n
Kulyashov Mikhail<\/td>Metabolic modeling of the production of a recombinant protein by methanotrophs<\/a><\/td>8.4 Modeling and computational analysis of microbiological systems and processes<\/td>\n<\/tr>\n
Sheremetieva Marina<\/td>L-Valine supersynthesis in edited Corynebacterium glutamicum cells and the reasons for its instability<\/a><\/td>8.3 Industrial biotechnology: creation of producer strains<\/td>\n<\/tr>\n
Titov Igor<\/td>How RNA secondary structure free energy landscape of ilvBNC operon transcriptional attenuator drives Corynebacterium glutamicum valine production<\/a><\/td>8.3 Industrial biotechnology: creation of producer strains<\/td>\n<\/tr>\n
Polyakova Elena<\/td>Microbial community diversity and metabolic potential in the Shulgan-Tash Cave: insights from metabarcoding and metagenomics<\/a><\/td>8.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Revel Muroz Anastasia<\/td>Hi-C metagenomic study of antimicrobial resistance genes spread in critically ill patients<\/a><\/td>8.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Ishmanov Tagir<\/td>Pipeline for processing metabarcoding data of fungi from natural communities<\/a><\/td>8.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Petrushin Ivan<\/td>Microbiome manipulation of potato with biostimulator Rhodococcus qingshengii VKM Ac2784D<\/a><\/td>8.2 Microbial communities of natural and anthropogenic habitats<\/td>\n<\/tr>\n
Klimina Ksenia<\/td>Impact of lactobacilli and bifidobacteria on mouse gut microbiota: comparative analysis of sequencing methods using Illumina and Oxford Nanopore Technologies platforms<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Mikhanoshina Natalya<\/td>New aspects in the study of lactobacilli<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Marsova Maria<\/td>Development of algorithms and approaches for the study of promising pharmaceutical strains using omix technologies<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Stavrovskaya Alla<\/td>\u042d\u0444\u0444\u0435\u043a\u0442\u044b \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0431\u0438\u043e\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0448\u0442\u0430\u043c\u043c\u0430 U21 \u0432 \u043a\u043e\u043c\u0431\u0438\u043d\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u044f\u0445 \u043f\u0430\u0440\u043a\u0438\u043d\u0441\u043e\u043d\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0441\u0438\u043d\u0434\u0440\u043e\u043c\u0430 \u0443 \u043a\u0440\u044b\u0441<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Galanova Olesya O<\/td>Application of machine learning algorithms to study the gut microbiota of patients with depressive disorders<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Valeria Fedorets<\/td>The gut virome of healthy people and patients with ulcerative colitis: diversity and antimicrobial potential<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Rustem A Ilyasov<\/td>Honey is a natural metatbiotic (postbiotic) product<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Olekhnovich Evgenii<\/td>Predicting biological mechanisms of gut microbial influence on melanoma immunotherapy outcomes using metagenomic data<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Zakharzhevskaya Natalya<\/td>Functional metabolomics in inflammatory bowel diseases<\/a><\/td>8.1 Biotechnology through the lens of the microbiome<\/td>\n<\/tr>\n
Tatiana Usenko<\/td>Targets for therapy of Parkinson's disease based on transcriptome analysis of the substance nigra of a mouse model with MPTP-induced parkinsonism and glucocerebrosidase dysfunction<\/a><\/td>7.3 Neurogenomics and genetics of behavior<\/td>\n<\/tr>\n
Olga Tarasova<\/td>An analysis of major depressive disorders using automated text analysis<\/a><\/td>7.3 Neurogenomics and genetics of behavior<\/td>\n<\/tr>\n
Shalaginova Irina<\/td>Differential gene expression and neuroimmune responses in the amygdala of rat strains with high and low nervous system excitability<\/a><\/td>7.3 Neurogenomics and genetics of behavior<\/td>\n<\/tr>\n
Korolenko Tatiana Alexandrovna<\/td>Db\/db mice as diabetes genetic model;effect of trehalose, comparative study of liver, heart and brain<\/a><\/td>7.2 Animal genetic models of human pathologies on vertebrates and invertebrates<\/td>\n<\/tr>\n
Pupyshev Alexander Borisovich<\/td>New avenues for treatment with trehalose of mice with pharmacological and transgenic models of Alzheimer's disease<\/a><\/td>7.2 Animal genetic models of human pathologies on vertebrates and invertebrates<\/td>\n<\/tr>\n
Urin Avel<\/td>Phylogenetic analysis of the genomes of several sexual and parthenogenetic lizards of the genus Darevskia<\/a><\/td>7.1 Genomics, genetics and systems biology of animals<\/td>\n<\/tr>\n
Galina Arbuzova<\/td>Search and analysis of sequences encoding phenoloxidases of the endemic Baikal amphipod species Eulimnogammarus verrucosus<\/i><\/a><\/td>7.1 Genomics, genetics and systems biology of animals<\/td>\n<\/tr>\n
Zamalutdinov Aleksei<\/td>Cost-effective estimation of optimal number of reads in GBS sequencing<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Asan Emirsaliev<\/td>A unified data preprocessing framework to address inconsistencies in comparative plastid genome studies<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Konstantin Kozlov<\/td>Genomic prediction in plants using machine learning<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Yawar Habib<\/td>Identification of subpopulation in Russian soybean germplasm collection using advanced genetic methods<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Svetlana Afonnikova<\/td>Genome-wide association study reveals novel loci modulating pre-harvest sprouting and grain color in red-grained winter wheat T. aestivum L.<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Stanin Vladislav<\/td>Genetic diversity shaped by transposon variation in chickpea<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Zykova Tatyana<\/td>Restoring the function of the HvMyc2 gene, which controls the blue color of barley grain, through its targeted modification<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Sidorenko Aleksandra<\/td>Regulation of MAKR6 gene activity in Arabidopsis thaliana L. root<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Antonina Kiseleva<\/td>Functional characterization of genes with daily expression patterns in common wheat<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Victoria Kharchenko<\/td>Floral boundaries are sliding inside of inflorescences Arabidopsis thaliana with mutation of the gene APETELA1-1<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Vodiasova Ekaterina<\/td>The transcription factor WRKY multigene family in grapevine (Vitis vinifera): genome-wide identification and evolution<\/a><\/td>6 Genetics\/genomics, bioinformatics and systems biology of plants<\/td>\n<\/tr>\n
Voronina Olga<\/td>The contribution of molecular phylogenetic methods to the control of the diversity of the lung microbiome in patients with cystic fibrosis during complex therapy<\/a><\/td>5.2 Molecular phylogenetics and phylogenomics of Plants, Fungi, Protists, Prokaryotes and Viruses<\/td>\n<\/tr>\n
Rybina Anna<\/td>Phylogenetic analysis and molecular dynamic simulations of CsqR, a transcription factor from Escherichia coli<\/a><\/td>5.2 Molecular phylogenetics and phylogenomics of Plants, Fungi, Protists, Prokaryotes and Viruses<\/td>\n<\/tr>\n
Smirnov Alexey<\/td>Single-cell genomics \u2013 a powerful tool to resolve the phylogeny of uncultivable species of Amoebozoa<\/a><\/td>5.2 Molecular phylogenetics and phylogenomics of Plants, Fungi, Protists, Prokaryotes and Viruses<\/td>\n<\/tr>\n
Kamyshatskaya Oksana<\/td>Molecular phylogeny of amoeba familly Amoebidae (Euamoebida, Tubulinea, Amoebozoa)<\/a><\/td>5.2 Molecular phylogenetics and phylogenomics of Plants, Fungi, Protists, Prokaryotes and Viruses<\/td>\n<\/tr>\n
Chadaeva Irina<\/td>A principal components analysis and functional annotation of differentially expressed genes in brain regions of gray rats selected for tame or aggressive behavior<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Trapezov Oleg<\/td>Consequences of 26 generations of selection in minks (Neogale vison<\/i>) on defensive reaction towards man<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Janko Skok<\/td>Testing the 'parasite-mediated domestication' hypothesis: a comparative approach to the wild boar and domestic pig as model species<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Yury Gusarov<\/td>Hydrophobic and aerophobic mitochondrial mutational spectrum of birds<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Kusliy Mariya<\/td>Preliminary results of determining the mitochondrial genetic diversity of Ovodov horses in Southern Siberia<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Baiandina Iuliia<\/td>Ctenophore opsins from Cydippida: phylogeny, structure, and potential ability for photoreception<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Lyudmila Zakharenko<\/td>The cytotype instability of the Drosophila melanogaster lines does not depend on the Pelement during intraspecific hybrid dysgenesis<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Irina Viktorovna Lazebnaya<\/td>Polymorphism of a number of candidate genes for economically important quantitative traits in the Kostroma cattle breed and its association with productive traits<\/a><\/td>5.1 Population and evolutionary genetics\/genomics of wild and domestic animals<\/td>\n<\/tr>\n
Timoshchuk Anna<\/td>A genome-wide association study of the plasma Nglycome in 10,000 individuals identifies 16 novel loci and highlights glycan-associated human traits<\/a><\/td>4.3 Genome-wide association studies<\/td>\n<\/tr>\n
Elgaeva Elizaveta<\/td>Testing the potential of antihypertensive drugs for spinal pain treatment<\/a><\/td>4.3 Genome-wide association studies<\/td>\n<\/tr>\n
Khvorykh Gennady<\/td>The performance of machine learning approach in genomewide association study of disease<\/a><\/td>4.3 Genome-wide association studies<\/td>\n<\/tr>\n
Belonogova Nadezhda<\/td>Efficiency of a new multi-trait approach applied to back pain-related phenotypes<\/a><\/td>4.3 Genome-wide association studies<\/td>\n<\/tr>\n
Berdnikova Anna<\/td>Identification of the optimal reference panel for the imputation of genotype data from the Russian sample on the example of the RuDDS cohort<\/a><\/td>4.3 Genome-wide association studies<\/td>\n<\/tr>\n
Rozanova Irina<\/td>Genetic dissection of spike productivity traits in spring barley<\/a><\/td>4.3 Genome-wide association studies<\/td>\n<\/tr>\n
Leonid Penkin<\/td>MGI Comprehensive Solution for Whole Genome, Exome, and Metagenomic Analysis from MGI<\/a><\/td>4.1 Population and evolutionary human genomics\/genetics<\/td>\n<\/tr>\n
Bushueva Olga<\/td>Genes encoding Hero proteins and ischemic stroke risk: a comprehensive moleculargenetic and bioinformatics analysis<\/a><\/td>4.1 Population and evolutionary human genomics\/genetics<\/td>\n<\/tr>\n
Prostakishina Elizaveta<\/td>Spatial transcriptional landscape of early-onset tongue cancer<\/a><\/td>4.1 Population and evolutionary human genomics\/genetics<\/td>\n<\/tr>\n
Vladimir Kharkov<\/td>Phylogeny and phylogeography of the Y-chromosome haplogroup N1a1a1a1a-F1419<\/a><\/td>4.1 Population and evolutionary human genomics\/genetics<\/td>\n<\/tr>\n
Proshakov Prokhor<\/td>Investigation of associations between aggressive behavior traits and genetic loci in a sample of contemporary armenian population representatives<\/a><\/td>4.1 Population and evolutionary human genomics\/genetics<\/td>\n<\/tr>\n
Radzhabov Magomed Osmanovich<\/td>Differences Between Ethnic Groups in Dagestan Based on Ychromosomal Lines and Autosomal SNPs<\/a><\/td>4.1 Population and evolutionary human genomics\/genetics<\/td>\n<\/tr>\n
Shpakov Alexander<\/td>Basic principles of allosteric regulation of hormonal receptors coupled to G proteins<\/a><\/td>3.2 Pharmacology, cheminformatics and chemical biology<\/td>\n<\/tr>\n
Biziukova Nadezhda<\/td>Application of text mining methods to extract comprehensive information about the biological activity of drugs: case-study for antiviral compounds<\/a><\/td>3.2 Pharmacology, cheminformatics and chemical biology<\/td>\n<\/tr>\n
Tarasova Olga<\/td>An analysis of virus-host interaction: case study for HIVinfection<\/a><\/td>3.2 Pharmacology, cheminformatics and chemical biology<\/td>\n<\/tr>\n
Vasilieva Asya<\/td>A GC-MS Chemotaxonomic Study on Lipophilic Compounds in the Leaves of Triticum aestivum<\/i> L.<\/a><\/td>3.2 Pharmacology, cheminformatics and chemical biology<\/td>\n<\/tr>\n
Sobolevsky Alexandr<\/td>Gating and regulation of ionotropic glutamate receptors<\/a><\/td>3.1 Structural biology of proteins, nucleic acids and membranes<\/td>\n<\/tr>\n
Efremov Roman<\/td>\u201cDynamic molecular portrait\u201d approach in computational structural biology of membrane proteins<\/a><\/td>3.1 Structural biology of proteins, nucleic acids and membranes<\/td>\n<\/tr>\n
Burtseva Anna<\/td>Structural studies of the LH2 and LH1-RC light-harvesting complexes from the purple sulfur bacterium Ectothiorhodospira haloalkaliphila<\/i><\/a><\/td>3.1 Structural biology of proteins, nucleic acids and membranes<\/td>\n<\/tr>\n
Mariasina Sofia<\/td>Protein-interacting C2H2-type zinc fingers: structural studies by NMR<\/a><\/td>3.1 Structural biology of proteins, nucleic acids and membranes<\/td>\n<\/tr>\n
Konarev Petr V<\/td>Methods for the analysis of small-angle X-ray scattering data from multicomponent biomolecular systems<\/a><\/td>3.1 Structural biology of proteins, nucleic acids and membranes<\/td>\n<\/tr>\n
Shaitan Konstantin<\/td>On the physical basis of the amino acid code for the 3D structure of proteins<\/a><\/td>3.1 Structural biology of proteins, nucleic acids and membranes<\/td>\n<\/tr>\n
Kaminskiy Grigory<\/td>\u041c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f \u044d\u043f\u0438\u0434\u0435\u043c\u0438\u043e\u043b\u043e\u0433\u0438\u044f 2024 - \u0447\u0442\u043e \u043d\u043e\u0432\u043e\u0433\u043e?<\/a><\/td>2.3 Mathematical epidemiology<\/td>\n<\/tr>\n
Krivorotko Olga<\/td>The forecasting of the COVID-19 spread in Russian Federation regions based on conditional generative adversarial network<\/a><\/td>2.3 Mathematical epidemiology<\/td>\n<\/tr>\n
Petrakova Viktoria<\/td>Optimal control models for solving problems of mathematical epidemiology<\/a><\/td>2.3 Mathematical epidemiology<\/td>\n<\/tr>\n
Leonenko Vasiliy<\/td>\u041c\u0435\u0442\u043e\u0434\u044b \u044d\u043a\u043e\u043d\u043e\u043c\u0438\u0447\u043d\u043e\u0433\u043e \u0438\u043d\u0434\u0438\u0432\u0438\u0434\u0443\u0443\u043c-\u043e\u0440\u0438\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0433\u043e \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0433\u043e\u0440\u043e\u0434\u0441\u043a\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0432 \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u0438\u0437\u0443\u0447\u0435\u043d\u0438\u044f \u043c\u043d\u043e\u0433\u043e\u043b\u0435\u0442\u043d\u0435\u0439 \u0434\u0438\u043d\u0430\u043c\u0438\u043a\u0438 \u0433\u0440\u0438\u043f\u043f\u0430 \u0432 \u0433\u043e\u0440\u043e\u0434\u0430\u0445 \u0420\u0424<\/a><\/td>2.3 Mathematical epidemiology<\/td>\n<\/tr>\n
Marko Djordjevic<\/td>Modeling bistable dynamics of bacterial restriction-modification systems to understand bacterial defense systems<\/a><\/td>2.2 Computational analysis and modeling of population, ecological and genetic systems and processes<\/td>\n<\/tr>\n
Bratus Alexander<\/td>Dynamics of population with consecutive mutation of genotypes<\/a><\/td>2.2 Computational analysis and modeling of population, ecological and genetic systems and processes<\/td>\n<\/tr>\n
Bojana Ilic<\/td>Integrated mathematical modeling, experimental and bioinformatics study of Type-II antitoxin-toxin system's response to antibiotic exposure<\/a><\/td>2.2 Computational analysis and modeling of population, ecological and genetic systems and processes<\/td>\n<\/tr>\n
Ediev Dalkhat<\/td>Demographics of genetic admixture and expansion<\/a><\/td>2.2 Computational analysis and modeling of population, ecological and genetic systems and processes<\/td>\n<\/tr>\n
Kolodkin Alexey<\/td>Biology of next epidemics: 3 dimensions of emergence and ORCHESTRA experience<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of gene networks and metabolic pathways<\/td>\n<\/tr>\n
Ashniev German A<\/td>Genomics-based Reconstruction of Chitin and Xanthan Oligo-saccharides Degradation Pathways in the Human Gut Microbiome<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of gene networks and metabolic pathways<\/td>\n<\/tr>\n
Kanapin Alexander<\/td>Retrotransposons expression controls: hubs and networks<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of gene networks and metabolic pathways<\/td>\n<\/tr>\n
Popov Daniil<\/td>Disuse-induced transcriptomic changes vary in different skeletal muscles: common and unique mechanisms<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Borvinskaya Ekaterina<\/td>Antibacterial Activity of Rainbow Trout Plasma: In Vitro<\/i> Assays and Proteomic Analysis<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Klimina Ksenia<\/td>Transcriptional Responses of Lacticaseibacillus rhamnosus<\/i> to IL-8 and IL-10 Cytokines<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Shcherbakova Anastasia<\/td>ACME HS dissociation: an adaptable cell fixationdissociation method for freshfrozen human adrenal gland tissues for scRNA-seq<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Bezuglov Vitalik<\/td>Approaches for sRNA Analysis of Human RNA-Seq Data: Comparison, Benchmarking<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Kuznetsov Vladimir<\/td>Roles of the transcriptional Rloop forming sequences (RLFS) and RLFS(+)R-loops in normal and cancer cell states. Critical review<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Deryuzhenko Maksim<\/td>Search and identification of differentially expressed Drosophila melanogaster<\/i> heat stress response genes with a low degree of expression change<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Pronozin Artem<\/td>Pan-transcriptome-based long non-coding RNAs prediction and analysis<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Prazyan Alexander<\/td>Molecular Mechanisms of Barley Cell Wall Response to Different Types of Ionising Radiation<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Chadaeva Irina<\/td>Ontology analysis of big transcriptomic data and differential gene expression<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Evdokimova Alexandra<\/td>Exploring Tissue-Specific Effects of 20-Hydroxyecdysone Through E23 Hormone Transporter Expression in Drosophila<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Gruntenko Nataly<\/td>Drosophila melanogaster<\/i> transcriptome response to Wolbachia<\/i> infection<\/a><\/td>1.4 Genome-wide transcriptomics (differential gene expression)<\/td>\n<\/tr>\n
Shevelyov Yuri<\/td>Disruption of inter-nucleosomal interactions leads to notable changes in genome architecture<\/a><\/td>1.3 Fundamental and applied 3D-genomics<\/td>\n<\/tr>\n
Pletenev Ilya<\/td>3D structure of long-range neuronal polycomb interactions in the human brain cortex<\/a><\/td>1.3 Fundamental and applied 3D-genomics<\/td>\n<\/tr>\n
Lagunov Timofey<\/td>Modeling spatial organization of lamp brush chromosomes<\/a><\/td>1.3 Fundamental and applied 3D-genomics<\/td>\n<\/tr>\n
Krasikova Alla<\/td>Monogenic and multigenic transcription loops in lampbrush chromosomes of birds<\/a><\/td>1.3 Fundamental and applied 3D-genomics<\/td>\n<\/tr>\n
Kabirova Evelyn<\/td>Cohesin degradation effect on mechanical properties of human colon tumor cells<\/a><\/td>1.3 Fundamental and applied 3D-genomics<\/td>\n<\/tr>\n
Grinenko Tatyana<\/td>Dormancy regulation of hematopoietic stem cells<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Levitsky Victor G<\/td>MetArea tool for predicting structural variability and cooperative binding of transcription factors in ChIPseq data<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Tsukanov Anton Vitalievich<\/td>Identification of potential transcription factors from whole transcriptome data by taking into account enrichment and classification of motifs of known transcription factors, and their expression levels<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Konstantin Yuditskiy<\/td>Unlocking DNA methylation with BSXplorer<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Bespalova Alina<\/td>The role of non-coding RNAs in the epigenetic conversion of gene loci<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Buyan Andrey<\/td>Tissue-specific and allele- specific activity of transcribed gene regulatory elements in human skeletal muscle<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Penzar Dmitry<\/td>Machine learning for rational design and reliable prediction of activity of gene regulatory regions<\/a><\/td>1.2 Regulatory genomics<\/td>\n<\/tr>\n
Zhimulev Igor<\/td>Developmental and housekeeping genes in the genome of Drosophila melanogaster<\/i><\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Daria Dibrova<\/td>COGcollator 2.0: an improved web server for analysis of distant relationships between homologous protein families<\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Eugene Korotkov<\/td>Bacterial genomes are internally formatted<\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Romanenko Svetlana<\/td>Relevance of integration of cytogenetics data and chromosome length genome assemblies at the example of various vertebrates` groups<\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Konanov Dmitry<\/td>Systematic analysis of tandem genome amplification events in Yersinia pestis<\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Rudenko Valentina<\/td>Structural organization of the eukaryotic genome by example of C. merolae<\/i><\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Irina Makarova<\/td>Non-B DNA Structures Adjacent to Ultraconserved Non-Coding Elements Unveiled<\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Shipova Aleksandra<\/td>Deciphering the structural organization of sex chromosomes in Siberian silk moth, Dendrolimus sibiricus<\/i><\/a><\/td>1.1 Structural-functional organization of genomes<\/td>\n<\/tr>\n
Vladimir Ivanisenko<\/td>Automated reconstruction and analysis of gene networks using cognitive system ANDSystem.<\/a><\/td>2.1 Reconstruction, computational analysis and modeling of gene networks and metabolic pathways<\/td>\n<\/tr>\n
Tatyana Kolesnikova<\/td>Polytene chromosomes as a tool to identify factors influencing the efficiency of DNA replication initiation.<\/a><\/td>11.1 DNA replication and repair<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":3967,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/pages\/3974"}],"collection":[{"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/users\/3967"}],"replies":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/comments?post=3974"}],"version-history":[{"count":10,"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/pages\/3974\/revisions"}],"predecessor-version":[{"id":4002,"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/pages\/3974\/revisions\/4002"}],"wp:attachment":[{"href":"https:\/\/bgrssb.icgbio.ru\/2024\/wp-json\/wp\/v2\/media?parent=3974"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}