Biyokimyasal Reaksiyonlar için Stokastik Simülasyon Algoritmalarına Genel Bir Bakış

Biyolojik bir sistemi anlayabilmek için hangi genlerin/proteinlerin organizmanın neresinde, ne zaman ve nasıl reaksiyonda olduğunu bilmemiz gerekmektedir. Bu kadar detaylı, karmaşık ve metabolik seviyede rassal olan reaksiyonları içeren biyokimyasal bir mekanizmada, hücresel aktivitelerin deneysel olarak ispatlanması, teknolojik imkanların sınırlı olması sebebiyle çoğu kez mümkün olmamakta veya yüksek deney maliyetine sebep olmaktadır. Biyokimyasal modelleme; bir sistemin elemanlarının farklı zaman ve şartlar altındaki durumunu, sistemi oluşturan proteinler ve moleküller arasındaki etkileşimi sistemin bilinen özellikleri yardımıyla ifade etmenin matematiksel yoludur. Bu çalışmada; reaksiyonların nasıl formülize edildiği ve bu reaksiyonlardan oluşan sistemin stokastik modellemelerinin biyoinformatik ve matematiksel biyoloji alanlarında hangi simülasyon algoritmalarıyla yapıldığı tanıtılmaktadır.

Anahtar Kelimeler:

Matematiksel modelleme, Simülasyon, Stokastik algoritmalar

An Overview to Stochastic Simulation Algorithms for Biochemical Systems

In order to understand a biological system, we should know which genes/proteins react together, where, when, and how they react in the organisms. In such a biochemical mechanism which is detailed, complex, and stochastic in metabolic level, the experimental validations of cellular activations cannot be typically applicable due to the current technological limitations or the high expenses of the possible experiments. The biochemical modelling is a mathematical way to describe the elements of a system, their proteomic and metabolic interactions, their states under different time points and various conditions by using the known theories about that system. In this study we review how formalize the biochemical reactions and which simulation algorithms can be performed to stochastically model a system whose components are described by these biochemical reactions in the frameworks of bioinformatics and mathematical biology.

Keywords:

Mathematical modelling, Simulation, Stochastic algorithms,

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