Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Extension of leap condition in approximate stochastic simulation algorithms of biological networks with 2nd and 3rd order Taylor expansion
Date
2021-12-31
Author
Demirbüken, Saliha
Purutçuoğlu Gazi, Vilda
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
125
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/100927
Conference Name
2nd International Conference on Mathematics and Its Applications in Sci- ence and Engineering (ICMASE 2021)
Collections
Department of Statistics, Conference / Seminar
Suggestions
OpenMETU
Core
Extension of leap condition in approximate stochastic simulation algorithms of biological networks
Demibüken, Saliha; Purutçuoğlu Gazi, Vilda (2020-10-27)
Extension of Leap Condition in Approximate Stochastic Simulation Algorithms of Biological Networks
Demirbüken, Saliha; Purutçuoğlu Gazi, Vilda; Uğur, Ömür; Department of Scientific Computing (2021-9-08)
The approximate stochastic simulation (ASS) algorithms are the alternative approaches to generate the complex biological systems with a loss in accuracy by gaining from computational demand. There are a number of approximate methods which can successfully simulate the systems, such as poisson tau-leap and approximate Gillespie algorithms. The common property of these approaches is that they are based on the leap conditon which controls the change in hazard functions under a time interval. By means of this i...
Extension of Leap Condition in Approximate Stochastic Simulation Algorithms of Biological Networks
Demirbüken, Saliha; Purutçuoğlu Gazi, Vilda (2022-11-01)
Extension of the logistic equation with piecewise constant arguments and population dynamics
Altıntan, Derya; Akhmet, Marat; Department of Scientific Computing (2006)
Population dynamics is the dominant branch of mathematical biology. The first model for population dynamics was developed by Thomas Malthus. A more complicated model was developed by Pierre François Verhulst and it is called the logistic equation. Our aim in this thesis is to extend the models using piecewise constant arguments and to find the conditions when the models have fixed points, periodic solutions and chaos with investigation of stability of periodic solutions.
Extension of plurisubharmonic functions in the Lelong class
Yazıcı, Özcan (2014-01-01)
Let X be an algebraic subvariety of Cn and X be its closure in Pn. In their paper (J. Reine Angew. Math. 676 (2013), 33-49), Coman, Guedj and Zeriahi proved that any plurisub- harmonic function with logarithmic growth on X extends to a plurisubharmonic function with logarithmic growth on Cn when the germs (X, a) in Pn are irreducible for all a ∈ X\X. In this pa- per we consider X for which the germ (X, a) is reducible for some a ∈ X \X and we give a necessary and sufficient condition for X so that any pluri...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Demirbüken and V. Purutçuoğlu Gazi, “Extension of leap condition in approximate stochastic simulation algorithms of biological networks with 2nd and 3rd order Taylor expansion,” presented at the 2nd International Conference on Mathematics and Its Applications in Sci- ence and Engineering (ICMASE 2021), Salamanca, İspanya, 2021, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100927.