Mathematical Biology (steady states)

In summary: At the steady state $(u_5, v_5)$, the production of $v$ is balanced by the consumption, resulting in a constant value for $v$. This value is determined by the non-dimensional parameters $\overline{r}_{ba}$ and $\overline{r}_{ab}$. As for the value of $u$ at this steady state, it is determined by the non-dimensional parameters $\overline{\lambda}_{1}$, $\overline{d}$, and $\overline{r}_{ab}$, just like at the steady state $(u_4, v_4)$. However
  • #1
ra_forever8
129
0
non-dimensionalisation equation:
\begin{equation} \frac {du}{d\tau}=\frac{\overline{\lambda}_{1} u}{u+1} -\overline{r}_{ab}uv -\overline{d}u
\end{equation}
where $\overline{\lambda}_{1}= \frac {\lambda_{1}}{\lambda_{2} K_{1}}$
Another non-dimensionalisation equations
\begin{equation} \frac {dv}{d\tau}=(1-v) -\overline{r}_{ba}uv
\end{equation}
THE REAL QUESTION IS: calculate the steady state $(u_4,v_4)$ and $(u_5,v_5)$? Discuss the occurrence of these steady-states in respect of any relationships between the non-dimensional. Note you are not required to determine the stability of these two states.

=>
I have already calculated the steady-states of $(u_4,v_4)$ and $(u_5,v_5)$ which are
$(u_4,v_4)$ =($ \frac{\overline{\lambda}_{1} - \overline{d} -\overline{r}_{ab}}{\overline{r}_{ab} + \overline{d}} ,1)$
$(u_5,v_5)$ =($ \frac{\overline{\lambda}_{1} - \overline{d} -\overline{r}_{ab}}{\overline{r}_{ab} + \overline{d}}$ ,$ 1 - \overline{r}_{ba} \frac{\overline{\lambda}_{1} - \overline{d} -\overline{r}_{ab}}{\overline{r}_{ab} + \overline{d}}$ )

I HAVE ALREADY CALCULATED $(u_1,v_1)$ and $(u_2,v_2)$ and $(u_3,v_3)$ but i an not interested to talk about their steady-state with respect to non-dimensional parameters.

here are the non-dimensional parameters which I have also determined:
$\overline{\lambda}_{1}= \frac {\lambda_{1}}{\lambda_{2} K_{1}}$
$\overline{d}= \frac{d}{\lambda_{2}}$
$\overline{r}_{ab} = \frac{\overline{r}_{ab} K_{2}} {\lambda_{2}}$
$\overline{r}_{ba} = \frac{\overline{r}_{ab} K_{1}} {\lambda_{2}}$

can anyone please please help me in discussion of these steady states $(u_4,v_4)$ and $(u_5,v_5)$ with the above non-dimensional parameters .
 
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  • #2


Sure, let's discuss the steady states $(u_4, v_4)$ and $(u_5, v_5)$ in relation to the non-dimensional parameters.

First, let's look at the steady state $(u_4, v_4)$. This steady state occurs when the rate of change of $u$ and $v$ is equal to zero, meaning that the system has reached a stable equilibrium. Looking at the non-dimensional equation for $du/d\tau$, we can see that the first term on the right-hand side ($\overline{\lambda}_{1} u/(u+1)$) is proportional to $\overline{\lambda}_{1}$, which is determined by the ratio of the two rate constants ($\lambda_1$ and $\lambda_2$) and the equilibrium constant for the first reaction ($K_1$). This term represents the production of $u$ by the first reaction. The second term ($-\overline{r}_{ab}uv$) is proportional to both $\overline{r}_{ab}$ and $v$, and represents the consumption of $u$ by the second reaction. Finally, the third term ($-\overline{d}u$) is proportional to $\overline{d}$ and represents the degradation of $u$.

At the steady state $(u_4, v_4)$, the production of $u$ is balanced by the consumption and degradation, resulting in a constant value for $u$. This value is determined by the non-dimensional parameters $\overline{\lambda}_{1}$, $\overline{d}$, and $\overline{r}_{ab}$. Similarly, the steady state value of $v$ at $(u_4, v_4)$ is determined by the non-dimensional parameters $\overline{r}_{ba}$ and $\overline{r}_{ab}$.

Now let's look at the steady state $(u_5, v_5)$. This steady state occurs when the rate of change of $v$ is equal to zero, but the rate of change of $u$ is not. This means that $u$ is still changing, but $v$ has reached a stable equilibrium. Looking at the non-dimensional equation for $dv/d\tau$, we can see that the first term on the right-hand side ($1-v$) represents the production of $v$ by the first reaction. The second term ($
 

FAQ: Mathematical Biology (steady states)

What is Mathematical Biology?

Mathematical Biology is a field of study that combines mathematical and computational tools with biological data and concepts to better understand biological systems and processes. It applies mathematical models and techniques to analyze and solve problems in biology, such as population dynamics, epidemiology, and biochemical reactions.

What are steady states in Mathematical Biology?

In Mathematical Biology, steady states refer to the equilibrium points of a dynamic system where the values of all variables remain constant over time. It is the point where the rates of change in all directions are zero, and the system is in a stable state. In other words, the system has reached a balance between its inputs and outputs, and there is no net change in the system's behavior.

How are steady states determined in Mathematical Biology?

Steady states in Mathematical Biology are determined by solving the system of differential equations that describe the behavior of the biological system. These equations represent the relationship between the variables and their rates of change over time. By setting the rates of change to zero, we can find the values of the variables at which the system is in equilibrium.

Why are steady states important in Mathematical Biology?

Steady states are essential in Mathematical Biology as they provide insights into the behavior and stability of biological systems. By studying the steady states, we can understand how changes in the system's parameters or inputs affect its dynamics and whether the system is capable of maintaining its equilibrium. Additionally, steady states can help us predict the long-term behavior of a system and identify critical points that may lead to changes or disruptions in the system.

What are some applications of steady states in Mathematical Biology?

Steady states have various applications in Mathematical Biology, including population dynamics, disease modeling, and metabolic pathways analysis. For example, in population dynamics, steady states can help predict the long-term behavior of a population, such as its growth or decline. In disease modeling, steady states can help identify the conditions under which a disease may become endemic or die out. In metabolic pathways analysis, steady states can help identify the optimal conditions for a biochemical reaction to occur and maintain its equilibrium.

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