International Multiconference “Bioinformatics of Genome Regulation and Structure\Systems Biology”

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Systems computational biology: analysis, mathematical modeling and information technologies symposium

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Systems computational biology: analysis, mathematical modeling and information technologies symposiumMathematical modeling of robust pattern formation in the Drosophila eye disc

Mathematical modeling of robust pattern formation in the Drosophila eye disc

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Svetlana Surkova1, Vitaly Gursky2, Konstantin Kozlov3, Sergey Nuzhdin4, Maria Samsonova5
1SPbPU, St. Petersburg, Russia, surkova_syu@spbstu.ru
2Ioffe Institute, St. Petersburg,Russia, gursky@math.ioffe.ru
3SPbPU, St. Petersburg, Russia, kozlov_kn@spbstu.ru
4USC, Los Angeles, USA, snuzhdin@usc.edu
5SPbPU, St. Petersburg, Russia, m.samsonova@spbstu.ru

We apply mathematical modeling approach to study mechanisms underlying the robust formation of periodic pattern during the Drosophila eye development. Model is fitted to the preliminary quantitative data – concentrations of the main regulators of R8 cell selection and specification. We analyze how biological noise propagates within the model to explain the molecular mechanisms responsible for noise buffering.

Systems computational biology: analysis, mathematical modeling and information technologies symposiumPhase Portraits of Gene Networks Models

Phase Portraits of Gene Networks Models

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Natalia Ayupova1, Vladimir Golubyatnikov2, Vyacheslav Gradov3, Liliya Minushkina4
1Lab. of inverse problems of mathematical physics. Sobolev Institute of Mathematics SB RAS, ayupova@math.nsc.ru
2Lab. of inverse problems of mathematical physics. Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia, vpgolubyatn@gmail.com
3Mechanical and mathematical department Novosibirsk State University Novosibirsk, Russia, v.gradov@g.nsu.ru
4Mechanical and mathematical department Novosibirsk State University Novosibirsk, Russia, l.minushkina@g.nsu.ru

We investigate geometric and combinatorial structures of phase portraits of dynamical systems considered as models of functioning of some circular gene networks. Invariant 2-dimensional piecewise linear surfaces constructed here allow to give full description of phase portraits of these models and to control their trajectories

Systems computational biology: analysis, mathematical modeling and information technologies symposiumMathematical Modeling of Allergenic Pollen Propagation in Atmospheric Layer

Mathematical Modeling of Allergenic Pollen Propagation in Atmospheric Layer

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Poster (download)

[pdf-embedder url=”https://bgrssb.icgbio.ru/wp-content/uploads/2020/07/297.pdf”]
Medveditsyna Olga Sergeevna1, Rychkov Sergey Leonidovich2, Shatrov Anatoly Victorovich3
1Kirov State Medical University, ossitnikova@yandex.ru
2Vyatka State University, rychkov@list.ru
3Kirov State Medical University, avshatrov1@yandex.ru

The quasi-two-dimensional model of impurity propagation early designed elsewhere is modified for transporting of allergenic plant pollen from spread forested areas in vicinity of a large city. The model includes consideration of mesoscale hydrothermodynamicalВ  processes in the lower atmosphere taking into accountВ  thermal nonuniformities of the underlying surface in the urban and suburban environs. The boundary conditions and the model coefficients are determined using the parametrization method. Some results of numerical calculations are presented. The calculations were performed using parallelized algorithms on the cluster supercomputer of the Vyatka State University. They show that, due to the action of an inhomogeneous horizontal temperature gradient in the lower atmosphere, vortex flows can be formed above populated areas.

 

Systems computational biology: analysis, mathematical modeling and information technologies symposiumDevelopment of a method for recognizing biomedical entities in the texts of scientific articles

Development of a method for recognizing biomedical entities in the texts of scientific articles

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Poster (download)

[pdf-embedder url=”https://bgrssb.icgbio.ru/wp-content/uploads/2020/07/170.pdf”]
Stepan Derevyanchenko1, Pavel Demenkov2
1Novosibirsk State University, sod97@yandex.ru
2The Federal Research Center Institute of Cytology and Genetics The Siberian Branch of the Russian Academy of Sciences, demps@bionet.nsc.ru

In this paper, we consider the problem of name entity recognition in the texts of biological scientific articles. Using a combination of machine learning methods allowed us to achieve high recognition quality indicators.

Systems computational biology: analysis, mathematical modeling and information technologies symposiumAn architecture-independent algorithm for microRNA target prediction

An architecture-independent algorithm for microRNA target prediction

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Natalya Fokina1, Alexander Grinev2
1Moscow State Medical University, retrospector@ispras.ru
2Moscow State Medical University, grinev.ab@1msmu.ru

Nowadays the research on RNA interference is a subject of growing interest. One of the most perspective directions of this research is the use of bioinformatics methods to predict possible interactions of microRNAs with their mRNA counterparts, which allows to increase the accuracy and efficiency of their confirmation using laboratory means. In spite of this fact, the existing tools are unable to meet all the needs of molecular biology. An example of a problem currently lacking an appropriate solution is the study of RNA interference between organisms belonging to different taxonomic groups, notably, in parasite-host systems. Parasites utilise the host cell as a source of nutrients and habitat; molecular genetic profiles of both participants of this interaction are subject to dynamic changes. In this paper we present a novel algorithm for detection of interactions involving RNA molecules in a wide range of organisms. The proposed solution exceeds the existing ones in several characteristics and, in our view, can be broadly used in molecular biology and bioinformatics.

Systems computational biology: analysis, mathematical modeling and information technologies symposiumA Model of one Central Regulatory Circuit

A Model of one Central Regulatory Circuit

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Tatyana Bukharina1, Andrey Akinshin2, Vladimir Golubyatnikov3, Dagmara Furman4
1Institute of Cytology and Genetics SB RAS, bukharina@bionet.nsc.ru
2Sobolev Institute of Mathematics SB RAS, Andrey.akinshin@gmail.com
3Sobolev Institute of Mathematics SB RAS, vpgolubyatn@gmail.com
4Institute of Cytology and Genetics SB RAS, furman@bionet.nsc.ru

Macrochaetes are sensor organs of the drosophila with a function of mechanoreceptors. An adult mechanoreceptor comprises four specialized cells. All these cells originate from the sensory organ precursor (SOP) cell. A characteristic feature of the SOP cell is the highest content of the proneural proteins ASC as compared with the surrounding cells. The accumulation of these proteins and maintenance of their amount in the SOP cell at a necessary level is provided by the gene network with the achaete-scute gene complex (AS-C) as its key component. The central regulatory circuit (CRC) controls the activity of this complex. The CRC activity comprises two phases differing in the time when they act. A specific feature of the second phase is the presence of PHYL protein, involved in degradation of proneural proteins. We propose a mathematical model for the CRC functioning as a regulator of the content of ASC proteins in the sensory organ precursor cell.

Systems computational biology: analysis, mathematical modeling and information technologies symposiumGene Network of Type 2 Diabetes: Reconstruction and Analysis

Gene Network of Type 2 Diabetes: Reconstruction and Analysis

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Zamyatin Vladimir Igorevich1, Mustafin Zakhar Sergeevich2, Matushkin Yury Georgievich3, Afonnikov Dmitry Arkadievich4, Klimontov Vadim Valerievich5, Lashin Sergey Aleksandrovich6
1Institute of Cytology and Genetics, Novosibirsk State University, zamyatin@bionet.nsc.ru
2Institute of Cytology and Genetics, Novosibirsk State University, mustafin@bionet.nsc.ru
3Institute of Cytology and Genetics, Novosibirsk State University, mat@bionet.nsc.ru
4Institute of Cytology and Genetics, Novosibirsk State University, ada@bionet.nsc.ru
5Institute of Cytology and Genetics, Novosibirsk State University, klimontov@mail.ru
6Institute of Cytology and Genetics, Novosibirsk State University, lashin@bionet.nsc.ru

Currently, due to the appearance of an increasing number of genomic, molecular, histological data, there is an intensive detailing of individual molecular genetic systems of the human body and phenotypic deviations caused by violations in one or more elements of these systems. At the same time, there is no, as such, a holistic understanding of the nature of the formation and course of type II diabetes, which includes a sufficient amount of available experimental data. In this study, we reconstructed gene networks of transcriptional regulation, functional connectivity, and protein-protein interactions for type 2 diabetes. Information on the evolutionary age of genes was superimposed on the network; it was shown that the genes in question are predominantly “evolutionarily old”. New genes have been found that were not previously associated with type 2 diabetes, such as PER1, PER3, ARHGEF4, genes whose homologues are associated with the onset of diabetes in mice – CLOCK, ARNTL (encoding transcription factors) – the goals for subsequent experimental confirmation. Validation of gene networks by analysis of tissue-specific expression has shown that most genes included in putative signal transduction pathways are expressed in the same tissues.

Systems computational biology: analysis, mathematical modeling and information technologies symposiumMathematical model of punctuated equilibrium evolution

Mathematical model of punctuated equilibrium evolution

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Vitaly A. Likhoshvai1, Tamara M. Khlebodarova2
1Institute Cytology and Genetics SB RAS, likho@bionet.nsc.ru
2Institute Cytology and Genetics SB RAS, tamara@bionet.nsc.ru

Fossil record of Earth describing the last 500 million years is characterized by evolution discontinuity as well as recurring global extinctions of some species and their replacement by new types, the causes of which are still not clear. We developed a model of evolution of Earth’s biota based on the universal laws of living systems functioning – self-reproduction, dependence of reproduction efficiency and mortality on biota density, mutational variability in the process of self-reproduction and selection of the most adapted individuals. We have shown that oscillatory dynamic of biota density is generated due to only these four factors in populations with sexual type reproduction. The same factors can explain such aspects of punctuated evolution observed in the fossil record as extinction catastrophes, rapid growth phases and stasis phases of species diversity. Therefore, both cyclic and intermittent dynamics of changes in the diversity of organisms with sexual reproduction that make up the Earth’s global ecosystem observed in the last 500 million years may well be explained solely by internal laws of self-development with no impact of external factors.

Systems computational biology: analysis, mathematical modeling and information technologies symposiumECM stiffness effects and subtumor formation in glioma growth. In Silico model

ECM stiffness effects and subtumor formation in glioma growth. In Silico model

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Vladimir Kalinin1
1R&D section, TMA, Dundalk, Ireland, vladimir.kalinin@tma-science.ie

This study is based on in silico model and demonstrates how variations of Extracellular Matrix (ECM) stiffness may affect glioma invasive scenarios. The model describes cell proliferation and transport through elastic and compressible cell- ECM composite, including “go/grow” transitions determined by oxygen concentrations.  Simulations generate invasive scenarios conditioned only by set of mechanical characteristics of cell-ECM composite typical for gliomas. Multicellular Tumor Spheroid (MTS) growing in soft matrix exhibits gentle cell density profile with elongated low density invasive zone, while rigid ECM conditions sharp edge of MTS and higher invasion speed. Moreover, the highest speed of tumor invasion is obtained at intermediate values of ECM stiffness, when a compact cell cluster is being formed instead of invasive zone as a second proliferative layer out of the core spheroid.

Systems computational biology: analysis, mathematical modeling and information technologies symposiumIntegration of transcriptomics data into a genome-scale metabolic model of the methanotrophic bacterium Methylotuvimicrobium alcaliphilum 20ZR

Integration of transcriptomics data into a genome-scale metabolic model of the methanotrophic bacterium Methylotuvimicrobium alcaliphilum 20ZR

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Mikhail Kulyashov1, Ivan S. Evshin2, Nikita V. Ivanisenko3, Semyon K. Kolmykov4, Tamara M. Khlebodarova5, Ilya R. Akberdin6
1BIOSOFT.RU, LLC ; Novosibirsk State University; FRC Institute of Cytology and Genetics SB RAS, m.kulyashov@mail.ru
2BIOSOFT.RU, LLC; Institute of Computational Technologies SB RAS, ivan@developmentontheedge.com
3FRC Institute of Cytology and Genetics SB RAS, n.ivanisenko@gmail.com
4BIOSOFT.RU, LLC; Institute of Computational Technologies SB RAS; FRC Institute of Cytology and Genetics SB RAS, semyonk@developmentontheedge.com
5FRC Institute of Cytology and Genetics SB RAS, tamara@bionet.nsc.ru
6BIOSOFT.RU, LLC; FRC Institute of Cytology and Genetics SB RAS; Novosibirsk State University, akberdinir@gmail.com

Aerobic methane-oxidizing bacteria or methanotrophs have the unique ability to grow on methane as their sole source of carbon and energy. The main metabolic steps of the methane utilization by microorganisms have been identified and well-studied to date. However, a detailed understanding of molecular genetic mechanisms that provide an adaptive response at the level of transcription regulation to various growth conditions, high and low pH, temperature, and salinity is still elusive. To solve the issue we have conducted a detailed theoretical study of the molecular mechanisms of gene expression regulation in the bacterium Methylotuvimicrobium alcaliphilum 20ZR (hereinafter 20ZR) based on the integration of original omics data into genome-scale metabolic model of the 20ZR.