If you team competes in the [**Software & AI** village](https://competition.igem.org/participation/villages) or wants to
apply for the [**Best Software Tool** prize](https://competition.igem.org/judging/awards), you **MUST** host all the
code of your team's software tool in this repository, `main` branch. By the **Wiki Freeze**, a
[release](https://docs.gitlab.com/ee/user/project/releases/) will be automatically created as the judging artifact of
this software tool. You will be able to keep working on your software after the Grand Jamboree.
All the dry lab projects include some kind of programming: the model, the hardware, and the software tool. All code of these three parts are exhibited in our repository and are organized into the three directories:
> If your team does not have any software tool, you can totally ignore this repository. If left unchanged, this
repository will be automatically deleted by the end of the season.
```
|- hardware-2023
|- model-2023
|- software2023
```
Visit the corresponding directory and get an insight into the details of our code! Below is the description for each project.
## Hardware: NOX Kit
## Description
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might
be unfamiliar with (for example your team wiki). A list of Features or a Background subsection can also be added here.
If there are alternatives to your project, this is a good place to list differentiating factors.
NOX Kit is a general biology experiment environmental detection hardware kit that provides temperature control, temperature, and bioluminescence monitoring functions.
## Installation
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew.
However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing
specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a
specific context like a particular programming language version or operating system or has dependencies that have to be
installed manually, also add a Requirements subsection.
In this project, our bioamplifiers can amplify trace analytes and convert them into bioluminescence. Currently, expensive fluorescence microscopes are often required to detect bioluminescence reactions, which makes large-scale measurements difficult. To enable low-cost and high-throughput detection, we designed the NOX Kit to address this need.
## Usage
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of
usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably
include in the README.
NOX Kit has the following features (see the [[feature-description][Feature Description]] section for details):
## Contributing
State if you are open to contributions and what your requirements are for accepting them.
- Modular Design: Extensible configuration, add/remove modules by needs
For people who want to make changes to your project, it's helpful to have some documentation on how to get started.
Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps
explicit. These instructions could also be useful to your future self.
- Multiple Working Modules: Works standalone or in array for high-throughput
You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce
the likelihood that the changes inadvertently break something. Having instructions for running tests is especially
helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
- User-friendly Interface: Simple clicks to collect and visualize data in real time
## Authors and acknowledgment
Show your appreciation to those who have contributed to the project.
- Reproducible Low-Cost Design: Core board costs less than $1 (5 RMB). Streamlined for statble reproduction and mass production.
So for general users, NOX Kit is simple and easy to use - just connect and collect/visualize data. For developers, NOX Kit is low-cost and extensible - build upon it to create more low-cost, high-throughput biosensors.
[Click HERE to learn more about our hardware project!](https://gitlab.igem.org/2023/software-tools/ucas-china/-/tree/main/hardware-2023?ref_type=heads)
## Model:
Our model consists of five main parts. Accordingly, our contributions focus on three respects, that is, for our team, for the Biology Blocks Simulation associated with cybernetics, and for the open-source computer project, a diffusion visualization APP.
- The first part is for our team, we demonstrate the concept for our design. For the self-renewal design, we compare and model two circuits to show the tradeoff of effectiveness and renewability, thus for our wet lab to choose. For the digitalizer, we calculate the rough interval of the threshold of our digitalizer, design a series of experiments for our wet lab to locate the real threshold, and finally get the well-fitted data. We further estimated the repressor strength to be more than 10 in terms of the relative strength intervals we divided. For other data fitting, we calculate the decay coefficient of the luminescence, and according to the relation between the luminescence and the product, we can further get the coefficient of our product for our modeling. For the hardware group, we use COMSOL to build a simple 3D and 2D model to see the point diffusion, and thanks to the group-sensing response, we simplify the reaction in the container to be quick and complete. Then we can see the concentration in the container increases uniformly and rapidly.
- The second contribution is for the Biology Blocks Simulation associated with cybernetics. We have found differential equations and reaction chains in the fields of biology and automatic control. In the field of control theory, there are perfect time-domain frequency-domain transformation rules to get the solution of multiple series differential equations, so as to conveniently calculate the transfer function from input to output. We found the correspondence of these rules in the biological field and established our single input single output model to model our calibration curve. However, due to the ideal assumptions and inadequate parameters, our system can confirm different output levels for different inputs but cannot do accurate quantitative research.
- The third part is for the open-source computer project, we use basic physical rules to build a 2D diffusion model, to visualize this process, we innovately use the concept convolution in computer vision and use video frames to display. These are our first try. Further, we designed a perfect APP to realize the function of user-defined input diffusion initial concentration, real-time display of diffusion screen, and real-time calculation of cross-section material concentration at each moment.
All of our works are based on codes and softwares, and our codes are available in our appendix.
[Click HERE to learn more about our model project!](https://gitlab.igem.org/2023/software-tools/ucas-china/-/tree/main/model-2023?ref_type=heads)
## Software: Ask NOX
We designed an NLP-based search tool for iGEM standard parts, Ask NOX. Powered by Llama2 and BERT, it automatically summarizes the function and application of all the iGEM standard parts available on https://parts.igem.org and creates a mapping between iGEM standard part name and the "summary" of its functions by model training. When searching on the Ask NOX website, users can input all functions of their desired BioBrick using a sentence in natural language instead of keywords. This tool functions like ChatGPT, improving the efficiency of searching and helping find out the optimal BioBrick among the huge database.
The model we trained is now been open to the public. [Try our model NOW on this website!](http://rd.xjs.link)
This tool has been validated by our teammates and improved efficiency, so we hope that other teams can benefit from this tool when searching for a BioBrick. We also hope that this work can inspire other teams to explore the application of LLMs in a software project.
[Click HERE to learn more about our software project!](https://gitlab.igem.org/2023/software-tools/ucas-china/-/tree/main/software2023?ref_type=heads)
