Candan Çelik

Candan Çelik
Istanbul Aydin University · Department of Industrial Engineering

PhD

About

6
Publications
210
Reads
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9
Citations
Additional affiliations
September 2019 - June 2020
Comenius University Bratislava
Position
  • Graduate Teaching Assistant
Description
  • Markov processes I-II
Education
September 2018 - June 2022
Comenius University Bratislava
Field of study
  • Applied Mathematics
January 2014 - January 2016
Ege University
Field of study
  • Applied Mathematics
September 2009 - July 2013
Ege University
Field of study
  • Mathematics

Publications

Publications (6)
Chapter
Chemical reaction networks involving molecular species at low copy numbers lead to stochasticity in protein levels in gene expression at the single-cell level. Mathematical modelling of this stochastic phenomenon enables us to elucidate the underlying molecular mechanisms quantitatively. Here we present a two-stage stochastic gene expression model...
Chapter
Regulatory molecules such as transcription factors are often present at relatively small copy numbers in living cells. The copy number of a particular molecule fluctuates in time due to the random occurrence of production and degradation reactions. Here we consider a stochastic model for a self-regulating transcription factor whose lifespan (or tim...
Article
Full-text available
Background Stochastic modelling plays a crucial role in comprehending the dynamics of intracellular events in various biochemical systems, including gene-expression models. Cell-to-cell variability arises from the stochasticity or noise in the levels of gene products such as messenger RNA (mRNA) and protein. The sources of noise can stem from diffe...
Thesis
Mathematical models of biochemical processes are essential tools to understanding the dynamics of intercellular events in living organisms. The copy number of species in such a system fluctuates in time due to the random occurrence of chemical reactions, leading to variability in the population of living cells. Therefore, characterising the number...
Preprint
Full-text available
Chemical reaction networks involving molecular species at low copy numbers lead to stochasticity in protein levels in gene expression at the single-cell level. Mathematical modelling of this stochastic phenomenon enables us to elucidate the underlying molecular mechanisms quantitatively. Here we present a two-stage stochastic gene expression model...
Preprint
Full-text available
Regulatory molecules such as transcription factors are often present at relatively small copy numbers in living cells. The copy number of a particular molecule fluctuates in time due to the random occurrence of production and degradation reactions. Here we consider a stochastic model for a self-regulating transcription factor whose lifespan (or tim...

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