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Vespa - Biochip Design Verification Algorithm

Table of Contents

Overview

Continuous-Flow Microfluidic Devices (CFMDs), also known as biochips, provide automated and cost-effective solutions for biomolecular analysis in life science applications. Multi-step biochemical reactions have required incorporating microfluidic components into CFMDs, which may raise their design complexity and lead to Design-Objective-Constraint Compatibility (DOCC) conflicts. Existing validation methods excel in optimizing Control-Layer Pressurization Protocol (CLPP) for small networks. However, they face challenges in describing operation constraints for microfluidic large-scale integration (mLSI) experiments and addressing the leakage risk. For that, we developed Vespa, an open-source validation framework using logic expressions to describe operation constraints on a lower human labor cost. For each operation, taking an objective list, a constraint list, a design netlist, and a super-parameter as inputs, Vespa validates the DOCC by constructing a target fluid transportation path. In addition, it introduces a leakage risk mitigation mechanism, issuing warnings for incorrect constraints and potential fluid leakage risks. The work includes over 900 real-world and synthetic benchmarks in three complexity ranges to support researchers in the field. As a result, more than 85% of benchmark experiments yield correct results within 0.3 seconds, enabling Vespa for real-time validation and integration into interactive CFMD design tools. Finally, to show Vespa's practical efficacy and real-world impact, we created case studies using a real-world CFMD. We demonstrated that Vespa eliminates over 90% of DOCC-related wet lab tests by detecting issues and making updates before fabrication.

Install

Download the repository from GitHub, create a venv environment, and install the necessary packages. Here we use python3.8 as the python interpreter.

$ git clone https://github.com/zyrrron/VeSpA-Algorithm.git
$ cd Vespa-Algorithm
$ python3 -m venv venv/
$ venv/bin/pip3 install -r requirements.txt

After you install all the packages, you are able to run the algorithm.

Usage

Random Benchmarks

You can run this algorithm to test the given random benchmarks with this command:

$ venv/bin/python3 TestAlgorithm.py

If you want to generate random benchmarks by your self, you can use this command to generate random designs:

$ venv/bin/python3 RandomCaseGenerator.py

If it is the first time to test the random benchmarks, this command can automatically generate random Constraints by calling ConstraintMaker.py and save it for the next time:

$ venv/bin/python3 TestAlgorithm.py

All Experiment objectives for Random Constraints are set to ['F1', 'F2']. User can edit it in TestAlgorithm.py.

Literature Benchmarks

You can run this algorithm to test the given literature review benchmarks with this command:

$ venv/bin/python3 lrbtest.py

You can also create your own biochip design by editing LRB_new.py. And Create Constraint and Experiment objectives in Constraint_UR_lrb_new.csv.

Maintainers

@zyrrron.

Contributing

Feel free to dive in! Open an issue or submit PRs.

Contributors

This project exists thanks to all the people who contribute.

License

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