Evolution modeling algorithm of biochemical networks

Tatjana Rubina; Egils Stalidzans

Evolution modeling algorithm of biochemical networks

Tatjana Rubina
, Egils Stalidzans

Latvia University of Life Sciences and Technologies

Research output: Contribution to conference › Paper › peer-review

1 Citation (Scopus)

Abstract

Biological systems are extremely complex, nonlinear and self-organized, self-regulated systems that can adjust to the environmental changes due to underlying genetic mechanisms. The key task of systems biology is to understand cellular processes, functions and/or properties of biological system better. It can be done by means of the structure, behaviour and dynamic exploration of biochemical networks, such as genetic regulatory, metabolic, protein interaction and signalling networks. In this paper we focused on the modeling of biochemical networks evolution that occur as a result of genetic alterations and offer coterie an evolution modeling algorithm of biochemical network structure.

Original language	English
Pages	24-29
Number of pages	6
Publication status	Published - 2012
Externally published	Yes
Event	2012 10th International Industrial Simulation Conference, ISC 2012 - Brno, Czech Republic Duration: 4 Jun 2012 → 6 Jun 2012

Conference

Conference	2012 10th International Industrial Simulation Conference, ISC 2012
Country/Territory	Czech Republic
City	Brno
Period	4/06/12 → 6/06/12

Keywords

Biochemical networks
Evolution modeling
Feedback
Mutation operators

Cite this

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title = "Evolution modeling algorithm of biochemical networks",

abstract = "Biological systems are extremely complex, nonlinear and self-organized, self-regulated systems that can adjust to the environmental changes due to underlying genetic mechanisms. The key task of systems biology is to understand cellular processes, functions and/or properties of biological system better. It can be done by means of the structure, behaviour and dynamic exploration of biochemical networks, such as genetic regulatory, metabolic, protein interaction and signalling networks. In this paper we focused on the modeling of biochemical networks evolution that occur as a result of genetic alterations and offer coterie an evolution modeling algorithm of biochemical network structure.",

keywords = "Biochemical networks, Evolution modeling, Feedback, Mutation operators",

author = "Tatjana Rubina and Egils Stalidzans",

year = "2012",

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note = "2012 10th International Industrial Simulation Conference, ISC 2012 ; Conference date: 04-06-2012 Through 06-06-2012",

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T1 - Evolution modeling algorithm of biochemical networks

AU - Rubina, Tatjana

AU - Stalidzans, Egils

PY - 2012

Y1 - 2012

N2 - Biological systems are extremely complex, nonlinear and self-organized, self-regulated systems that can adjust to the environmental changes due to underlying genetic mechanisms. The key task of systems biology is to understand cellular processes, functions and/or properties of biological system better. It can be done by means of the structure, behaviour and dynamic exploration of biochemical networks, such as genetic regulatory, metabolic, protein interaction and signalling networks. In this paper we focused on the modeling of biochemical networks evolution that occur as a result of genetic alterations and offer coterie an evolution modeling algorithm of biochemical network structure.

AB - Biological systems are extremely complex, nonlinear and self-organized, self-regulated systems that can adjust to the environmental changes due to underlying genetic mechanisms. The key task of systems biology is to understand cellular processes, functions and/or properties of biological system better. It can be done by means of the structure, behaviour and dynamic exploration of biochemical networks, such as genetic regulatory, metabolic, protein interaction and signalling networks. In this paper we focused on the modeling of biochemical networks evolution that occur as a result of genetic alterations and offer coterie an evolution modeling algorithm of biochemical network structure.

KW - Biochemical networks

KW - Evolution modeling

KW - Feedback

KW - Mutation operators

UR - https://www.scopus.com/pages/publications/84893761915

M3 - Paper

AN - SCOPUS:84893761915

SP - 24

EP - 29

T2 - 2012 10th International Industrial Simulation Conference, ISC 2012

Y2 - 4 June 2012 through 6 June 2012

ER -

Evolution modeling algorithm of biochemical networks

Abstract

Conference

Keywords

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