English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The exploration of biochemical networks, such as gregulation, metabolic, protein interaction and signal transduction networks helps to understand better ce llular processes, properties and functions of biolo gical system. An important task of biological systems investigation is explora tion of biochemical networks evolution and dynamic changes of their structure under pressure of the mutations and natural selecti on that are mentioned as the main evolution forces. Proposed network growth models have been used to establish topological prop erties of biochemical networks, such as scale-free degree distribution, ultra- small-world property, centrality and modularity. Bu t they consider network evolution implicitly, gener ally and ignore important properties of biological systems. To demonstrate an d investigate the evolution course of biochemical n etworks structure caused by genetic mutations, chosen by natural selection and depending of the biological system properties, evol ution models are needed what takes into account these features. In this pap er evolution modelling procedure is introduced as w ell as algorithm of biochemical networks structure that occurs as a res ult of genetic alterations by pressure of natural sand takes into account different importance levels of biochemical processe s.

The procedure of evolution modelling of biochemical networks structure