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Dive into the research topics where Yury G. Matushkin is active.

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Featured researches published by Yury G. Matushkin.


BMC Bioinformatics | 2017

Orthoscape: a cytoscape application for grouping and visualization KEGG based gene networks by taxonomy and homology principles

Zakhar Sergeevich Mustafin; Sergey A. Lashin; Yury G. Matushkin; Konstantin V. Gunbin; Dmitry A. Afonnikov

BackgroundThere are many available software tools for visualization and analysis of biological networks. Among them, Cytoscape (http://cytoscape.org/) is one of the most comprehensive packages, with many plugins and applications which extends its functionality by providing analysis of protein-protein interaction, gene regulatory and gene co-expression networks, metabolic, signaling, neural as well as ecological-type networks including food webs, communities networks etc. Nevertheless, only three plugins tagged ‘network evolution’ found in Cytoscape official app store and in literature. We have developed a new Cytoscape 3.0 application Orthoscape aimed to facilitate evolutionary analysis of gene networks and visualize the results.ResultsOrthoscape aids in analysis of evolutionary information available for gene sets and networks by highlighting: (1) the orthology relationships between genes; (2) the evolutionary origin of gene network components; (3) the evolutionary pressure mode (diversifying or stabilizing, negative or positive selection) of orthologous groups in general and/or branch-oriented mode. The distinctive feature of Orthoscape is the ability to control all data analysis steps via user-friendly interface.ConclusionOrthoscape allows its users to analyze gene networks or separated gene sets in the context of evolution. At each step of data analysis, Orthoscape also provides for convenient visualization and data manipulation.


BMC Microbiology | 2016

Bacteriophages affect evolution of bacterial communities in spatially distributed habitats: a simulation study

Alexandra Igorevna Klimenko; Yury G. Matushkin; Nikolay A. Kolchanov; Sergey A. Lashin

BackgroundBacteriophages are known to be one of the driving forces of bacterial evolution. Besides promoting horizontal transfer of genes between cells, they may induce directional selection of cells (for instance, according to more or less resistance to phage infection). Switching between lysogenic and lytic pathways results in various types of (co)evolution in host-phage systems. Spatial (more generally, ecological) organization of the living environment is another factor affecting evolution. In this study, we have simulated and analyzed a series of computer models of microbial communities evolving in spatially distributed environments under the pressure of phage infection.ResultsWe modeled evolving microbial communities living in spatially distributed flowing environments. Non-specific nutrient supplied in the only spatial direction, resulting in its non-uniform distribution in environment. We varied the time and the location of initial phage infestation of cells as well as switched chemotaxis on and off. Simulations were performed with the Haploid evolutionary constructor software (http://evol-constructor.bionet.nsc.ru/).ConclusionSimulations have shown that the spatial location of initial phage invasion may lead to different evolutionary scenarios. Phage infection decreases the speciation rate by more than one order as far as intensified selection blocks the origin of novel viable populations/species, which could carve out potential ecological niches. The dependence of speciation rate on the invasion node location varied on the time of invasion. Speciation rate was found to be lower when the phage invaded fully formed community of sedentary cells (at middle and late times) at the species-rich regions. This is especially noticeable in the case of late-time invasion.Our simulation study has shown that phage infection affects evolution of microbial community slowing down speciation and stabilizing the system as a whole. This influencing varied in its efficiency depending on spatially-ecological factors as well as community state at the moment of phage invasion.


BMC Evolutionary Biology | 2015

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

Alexandra Igorevna Klimenko; Yury G. Matushkin; Nikolay A. Kolchanov; Sergey A. Lashin

BackgroundMultiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members.ResultsHaploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate.ConclusionIn spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members.


Bioinformatics | 2016

AltORFev facilitates the prediction of alternative open reading frames in eukaryotic mRNAs

Alexey V. Kochetov; Jens Allmer; Alexandra Igorevna Klimenko; Bulat S. Zuraev; Yury G. Matushkin; Sergey A. Lashin

Motivation: Protein synthesis is not a straight forward process and one gene locus can produce many isoforms, for example, by starting mRNA translation from alternative start sites. altORF evaluator (altORFev) predicts alternative open reading frames within eukaryotic mRNA translated by a linear scanning mechanism and its modifications (leaky scanning and reinitiation). The program reveals the efficiently translated altORFs recognized by the majority of 40S ribosomal subunits landing on the 5′‐end of an mRNA. This information aids to reveal the functions of eukaryotic genes connected to synthesis of either unknown isoforms of annotated proteins or new unrelated polypeptides. Availability and Implementation: altORFev is available at http://www.bionet.nsc.ru/AUGWeb/and has been developed in Java 1.8 using the BioJava library; and the Vaadin framework to produce the web service. Contact: [email protected]


PLOS ONE | 2018

Pluripotency gene network dynamics: System views from parametric analysis

Ilya R. Akberdin; Nadezda A. Omelyanchuk; S. I. Fadeev; Natalya E. Leskova; Evgeniya A. Oschepkova; Fedor V. Kazantsev; Yury G. Matushkin; D. A. Afonnikov; N. A. Kolchanov

Multiple experimental data demonstrated that the core gene network orchestrating self-renewal and differentiation of mouse embryonic stem cells involves activity of Oct4, Sox2 and Nanog genes by means of a number of positive feedback loops among them. However, recent studies indicated that the architecture of the core gene network should also incorporate negative Nanog autoregulation and might not include positive feedbacks from Nanog to Oct4 and Sox2. Thorough parametric analysis of the mathematical model based on this revisited core regulatory circuit identified that there are substantial changes in model dynamics occurred depending on the strength of Oct4 and Sox2 activation and molecular complexity of Nanog autorepression. The analysis showed the existence of four dynamical domains with different numbers of stable and unstable steady states. We hypothesize that these domains can constitute the checkpoints in a developmental progression from naïve to primed pluripotency and vice versa. During this transition, parametric conditions exist, which generate an oscillatory behavior of the system explaining heterogeneity in expression of pluripotent and differentiation factors in serum ESC cultures. Eventually, simulations showed that addition of positive feedbacks from Nanog to Oct4 and Sox2 leads mainly to increase of the parametric space for the naïve ESC state, in which pluripotency factors are strongly expressed while differentiation ones are repressed.


Archive | 2016

The Animal Domestication Experiment as a Model of the Evolutionary Process: A New Insight into Evolution Under Selection Targeting Regulatory Systems

Ludmila N. Trut; Yury E. Herbek; Oleg V. Trapezov; Sergey A. Lashin; Yury G. Matushkin; Arcady L. Markel; Nikolay A. Kolchanov

The paper considers the main results of the long-lasting experimental domestication of animals—foxes, minks and brown rats. The following important conclusions have been made. Fundamental to the domestication process is the intensive selection of animals for human-tolerant behavior and the capability to adapt to the emerging social structure “human—domestication object”. Intensive selection for behavior and, therefore, for the central regulatory systems, which control the functioning of the entire organism, leads to large amounts of variability in the population under domestication. Stress caused by rapid environmental changes, with its neurohormonal mechanisms of regulation of genetic processes, has an important role in the induction of variability. These considerations prompted Dmitry Belyaev, mutational variability is rendered neutral. Under directional (and destabilizing) selection, hidden mutational variability becomes exposed. If the regulatory circuits with negative feedback are lost, hidden genotypic variability becomes exposed and individuals with major phenotypic aberrations occur.


in Silico Biology | 2002

GeneNet Database: Description and Modeling of Gene Networks

N. A. Kolchanov; Eugenia A. Nedosekina; Elena A. Ananko; V. A. Likhoshvai; Nikolay L. Podkolodny; Alexander V. Ratushny; Irina L. Stepanenko; O. A. Podkolodnaya; E. V. Ignatieva; Yury G. Matushkin


international conference on bioinformatics | 2007

Simulation of Coevolution in Community by Using the "Evolutionary Constructor" Program

Sergey A. Lashin; Valentin V. Suslov; N. A. Kolchanov; Yury G. Matushkin


in Silico Biology | 2012

Haploid evolutionary constructor: New features and further challenges

Sergey A. Lashin; Yury G. Matushkin


Ecological Modelling | 2012

Computer modeling of genome complexity variation trends in prokaryotic communities under varying habitat conditions

Sergey A. Lashin; Yury G. Matushkin; Valentin V. Suslov; Nikolay A. Kolchanov

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Sergey A. Lashin

Novosibirsk State University

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Nikolay A. Kolchanov

Novosibirsk State University

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N. A. Kolchanov

Russian Academy of Sciences

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Valentin V. Suslov

Novosibirsk State University

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Alexey V. Kochetov

Novosibirsk State University

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Bulat S. Zuraev

Novosibirsk State University

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D. A. Afonnikov

Russian Academy of Sciences

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Dmitry A. Afonnikov

Novosibirsk State University

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E. V. Ignatieva

Russian Academy of Sciences

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