Optimal Control of Gene Mutation in DNA Replication
نویسندگان
چکیده
منابع مشابه
Optimal Control of Gene Mutation in DNA Replication
We propose a molecular-level control system view of the gene mutations in DNA replication from the finite field concept. By treating DNA sequences as state variables, chemical mutagens and radiation as control inputs, one cell cycle as a step increment, and the measurements of the resulting DNA sequence as outputs, we derive system equations for both deterministic and stochastic discrete-time, ...
متن کاملDNA replication checkpoint control.
The eukaryotic cell cycle comprises two critical phases, DNA replication (S phase) and the subsequent distribution of an equivalent genome to each of two daughter cells at mitosis (M phase). A signal transduction cascade called the replication checkpoint has evolved to ensure that M phase does not occur prior to the completion of S phase. The mitotic regulators targeted by this checkpoint have ...
متن کاملOptimal placement of origins for DNA replication.
DNA replication is an essential process in biology and its timing must be robust so that cells can divide properly. Random fluctuations in the formation of replication starting points, called origins, and the subsequent activation of proteins lead to variations in the replication time. We analyze these stochastic properties of DNA and derive the positions of origins corresponding to the minimum...
متن کاملTheory and practice of optimal mutation rate control in hamming spaces of DNA sequences
We investigate the problem of optimal control of mutation by asexual self-replicating organisms represented by points in a metric space. We introduce the notion of a relatively monotonic fitness landscape and consider a generalisation of Fisher’s geometric model of adaptation for such spaces. Using a Hamming space as a prime example, we derive the probability of adaptation as a function of repr...
متن کاملDNA for Optimal Control
We introduce Diffusion Network Adaptation (DNA), a framework for finding approximate solutions to continuous time, continuous state, continuous action optimal control problems. We present two reinforcement learning algorithms developed under this framework, one model based and the other model free. We test the algorithms in computer simulations and in a complex pneumatic humanoid robot that had...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Biomedicine and Biotechnology
سال: 2012
ISSN: 1110-7243,1110-7251
DOI: 10.1155/2012/743172