The replication begins at origins along the DNA.
In prokaryotic cells, which have a single circular chromosome, replication initiates at a single origin of replication and proceeds bidirectionally until the entire chromosome is copied. In contrast, eukaryotic cells have multiple linear chromosomes that replicate from multiple origins of replication simultaneously. The linear nature of eukaryotic chromosomes poses challenges during replication, such as the need to overcome end-replication problem and preserving telomeres.
A problem is typically posed in a form by defining the objective, constraints, and variables involved. This helps to structure the problem and guide the search for a solution using mathematical or computational techniques.
Eukaryotic cells overcome the problem of their large size through compartmentalization. They have membrane-bound organelles that segregate different cellular functions, allowing for efficient organization and coordination of activities. Additionally, eukaryotic cells utilize various transport systems, such as vesicles and the cytoskeleton, to facilitate movement of molecules and organelles within the cell.
The first step that both scientists and engineers use to approach a problem is to identify and define the problem clearly. This involves understanding the goals to be achieved, the constraints to be considered, and any requirements that need to be met. Clarity in defining the problem helps guide the subsequent steps in the problem-solving process.
Telomerase helps solve the problem of DNA replication by adding repetitive sequences to the ends of chromosomes, known as telomeres. This prevents the loss of important genetic information during each round of cell division. By preserving the length of telomeres, telomerase maintains the stability and integrity of chromosomes.
Eukaryotic organisms solve the problem of time constraints on replication of DNA by using multiple origins of replication along each chromosome. This allows for DNA replication to occur simultaneously at several points, speeding up the process. Additionally, eukaryotic cells have specialized enzymes and proteins that help ensure efficient and accurate replication of DNA.
In prokaryotic cells, which have a single circular chromosome, replication initiates at a single origin of replication and proceeds bidirectionally until the entire chromosome is copied. In contrast, eukaryotic cells have multiple linear chromosomes that replicate from multiple origins of replication simultaneously. The linear nature of eukaryotic chromosomes poses challenges during replication, such as the need to overcome end-replication problem and preserving telomeres.
Telomeres solve the end replication problem by extending the 3' end of the chromosome. Without them, the 3' end can't be replicated since replication is 5' to 3'.
There is no limit.
It is a programming problem in which the objective function is to be optimised subject to a set of constraints. At least one of the constraints or the objective functions must be non-linear in at least one of the variables.
financial constraints and lack of expansion
a mainframe computer is required
Infeasibility occurs in a linear programming problem when there is no solution that satisfies all the constraints simultaneously.
Four constraints should be taken in optimal placement of capacitor problem for voltage improvement using the Particle Swarm Optimization.
The end replication problem in eukaryotes refers to the challenge of replicating the ends of linear chromosomes, which leads to the loss of genetic material with each cell division. This impacts DNA replication by causing the gradual shortening of chromosomes over time, which can eventually lead to cell aging and potentially contribute to diseases like cancer.
In linear programming, infeasibility refers to a situation where no feasible solution exists for a given set of constraints and objective function. This can occur when the constraints are contradictory or when the feasible region is empty. Infeasibility can be detected by solving the linear programming problem and finding that no solution satisfies all the constraints simultaneously. In such cases, the linear programming problem is said to be infeasible.
A problem is typically posed in a form by defining the objective, constraints, and variables involved. This helps to structure the problem and guide the search for a solution using mathematical or computational techniques.