[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 7, Issue 4 (3-2021) ::
2021, 7(4): 398-412 Back to browse issues page
Dynamical Analysis of Yeast Cell Cycle Using a Stochastic Markov Model
Sajad Shafiekhani , Azam Sadat Fatemi, Gelayol Nazari Golpayegani, Seyed Yashar Banihashem, Amir Homayoun Jafari
Associate Professor, Department of Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences & Research Center for Biomedical Technologies and Robotics, Tehran, Iran
Abstract:   (359 Views)
Introduction: The cell cycle network is responsible of control, growth and proliferation of cells. The relationship between the cell cycle network and cancer emergence, and the complex reciprocal interactions between genes/proteins calls for computational models to analyze this regulatory network. Ample experimental data confirm the existence of random behaviors in the interactions between genes and proteins in gene regulatory networks. Genetic factors, regulatory dynamics at the microscopic level, transcription rates of genes, and many other factors that depend on variable environmental conditions cause random behaviors in the cell cycle network.
Method: The aim of this study was to present a stochastic Markov model to simulate interactions between proteins in a complex network of fission yeast cell cycle and to predict the dynamics of proteins. We used local sensitivity analysis to investigate the relationship between the weight of protein / gene interactions with the probabilities of phase transition in the cell cycle.
Results: Using this model, the probability of transition between different phases of the cell cycle in the presence of different levels of noise was investigated and it was proved that the cell cycle path has the highest probability among all possible pathways for the cell. By performing sensitivity analysis, the correlation between the weight of interactions between proteins and the probability of transition between different phases of the cell cycle was calculated.
Conclusion: Our local sensitivity analysis revealed that how perturbation on parameters affect the transition probabilities between subsequent cell cycle phases, so it suggests testable hypotheses in the experimental environments. Also, the model of this study proves the stability of the cell cycle in the presence of moderate levels of noise.
Keywords: Dynamic, Cell cycle, Fission yeast, Markov
Full-Text [PDF 1819 kb]   (117 Downloads)    
Type of Study: Original Article | Subject: Bioinformatics
Received: 2020/03/9 | Accepted: 2020/07/20
Audio File [MP3 1059 KB]  (15 Download)
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Shafiekhani S, Fatemi A S, Nazari Golpayegani G, Banihashem S Y, Jafari A H. Dynamical Analysis of Yeast Cell Cycle Using a Stochastic Markov Model. Journal of Health and Biomedical Informatics. 2021; 7 (4) :398-412
URL: http://jhbmi.ir/article-1-484-en.html


Volume 7, Issue 4 (3-2021) Back to browse issues page
مجله انفورماتیک سلامت و زیست پزشکی Journal of Health and Biomedical Informatics
Persian site map - English site map - Created in 0.03 seconds with 30 queries by YEKTAWEB 4312