Team:SEU/Model
Model
Computation Model
In this part, we provide our computation model in chemical reactions and prove the validity via kinetic analysis.
In our system, numerical values are represented by concentrations of certain species. Chemical reactions are simplified as formal reactions such as \(A+B \xrightarrow{k} C\). A formal reaction consists of reactants, products (A, B and C) and rate constant (\(k\)). For each computation operation, given initial concentrations of certain species as inputs, the outputs are representd by the concentration of another species in the system at the end of the reaction.
According to [1], formal reactions can be mapped to DNA strand displacement (DSD) reactions [2] without losing the kinetic features of the reaction. We borrow such a model in our project to implement calculation operations.
As only addition, subtraction and multiplication are required in our project, we only provide the implementation of such computation. For each calculation operation, we firstly provide formal reactions, then provide kinetic analysis and finally propose DSD revaction implementation. The analysis in our model is totally based on classic mass action kinetics.
Addition:
To implement addition, we utilize:
\(A_1 \xrightarrow{k_1} O,\quad A_2 \xrightarrow{k_2} O,... \quad A_n \xrightarrow{k_n} O\). Initial concentrations of reactants \(A_i\) of such reactions are considered inputs and the final concentration of product \(O\) represent our result. Such reactions calculate \([O](\infty)=\sum_{i=1}^n[A_i](0)\).
Proof:
\(\dfrac{d [A_i](t)}{d t}=-k_i[A_i](t) (i=1,2...n)\) \(\Rightarrow [A_i](t)=[A_i](0)e^{-k_it} (i=1,2...n)\), \(\dfrac{d [O](t)}{d t}=\sum_{i=1}^n k_i[A_i](t)\) \(\Rightarrow [O](t)=-(\sum_{i=1}^n[A_i](0)e^{-k_it})+\sum_{i=1}^n[A_i](0)\) \(\Rightarrow [O](\infty)=\sum_{i=1}^n[A_i](0)\). Thus addition is successfully implemented.
The DSD implementation:
Subtraction:
To build a subtractor, we use \(A+B \xrightarrow{k_1} \phi\). The result is the final concentration of A or B, depending on the initial concentration of A and B.
Proof:
Apparently, \([A](t)=[B](t)+\Delta \).
If \(\Delta \neq 0\), \(\dfrac{d [A](t)}{d t}=-[A](t)([A](t)-\Delta)\) \(\Rightarrow [A](t)=\dfrac{[A](0)\Delta}{-[A](0)+[A](0)e^{\Delta t}+\Delta e^{\Delta t}} (\Delta \neq 0).\) If \(\Delta > 0\), \([A](\infty)=\Delta\). Otherwise \([A](\infty)=0\).
If \(\Delta =0\), \([A](t)=\dfrac{[A](0)}{1+[A](0)t}\). \([A](\infty)=0\). Hence substraction is implemented.
The DSD implementation:
Multiplication:
To calculate concentration multiplication, we utilize \(\alpha \xrightarrow{k_1} \phi, A+B+\alpha \xrightarrow{k_2} A+B+\alpha+C\). It calculates \([C](\infty)=[A](0)\times[B](0)\).
Proof:
\(\dfrac{d [\alpha](t)}{d t}=-k_1[\alpha](t)\) \(\Rightarrow [\alpha](t)=[\alpha](0)e^{-k_1t},\) \(\dfrac{d [A](t)}{d t}=\dfrac{d [B](t)}{d t}=0, \dfrac{d [C](t)}{d t}=k_2[A](t)[B](t)[\alpha](t)\) \(\Rightarrow [C](\infty)=\int_0^\infty [A](0)[B](0)[\alpha](t)=k_2/k_1[\alpha](0)[A](0)[B](0)\). Hence multiplication is implemented.
The DSD implementation:
Compared to the formal reactions, there are some minor changes:
1. \(\alpha\) is canceled to reduce the number of reactants.
2. One of the reactants will be consumed.
Neuron Implementation
1. Input layer
Input layer calculates weighted summation of all input data, i.e. it calculates\(\sum_{i=1}^n w_ix_i\) where \(n\) is the number of inputs, \(w_i, x_i\) (\(i=1,2,...n\)) are weights and inputs, respectively.
References
[1] D. Soloveichik, G. Seelig, E. Winfree, "DNA as a universal substrate for chemical kinetics," Proceedings of the National Academy of Sciences, vol. 107, no. 12, pp. 5393–5398, 2010.