📌 Inspiration
What inspired your team to build this?
β-Galactosidase assays are used frequently in the field of synthetic biology to understand the fundamental aspects of transcription, the central dogma of biology. β-Galactosidase assays contain eight measurements, generated by spectrophotometers which generally export text files. for each sample tested and on average approximately 100 samples are tested per assay. Historically, the computation for the miller unit (the quantification of transcription) has been manually copying all outputs of the assay into an excel template to calculate this unit. Seemingly when faced with this method of calculation, we were inspired to make a program that could interpret the outputs without manually having to enter them in, significantly decreasing the amount of repetitive work needed for calculating miller unit values.
🔍 What it does
Our program asks the user to take three files of different file types. The first is a text file containing the initial absorbance values from a spectrophotometer measured before the experiment, the second is a text file containing the final absorbance values measured after the experiment, and the last is a csv file containing sample times. This data will be processed using the miller unit equation that is defined by taking the difference of absorbance values at λ = 420 and 550 over the difference of absorbance values at Absorbents values at λ = 900 and 1000 over the volume (0.1, a constant) multiplied by the initial concentration and the amount of time in seconds the experiment took. Our program will calculate the miller units (MU) described by this equation and output them with the given sample from which the miller unit was derived.
⚙️ How we built it
All code generated in this project was made using Python.
💪 Challenges we ran into
As two students currently enrolled in EECS 168, we faced many challenges through our development of this program. Initially, we lacked confidence in our abilities to achieve our goal. However, after clever problem solving, we were able to achieve our goal using the tools we knew (or had recently learned in this hackathon).
🌟 Accomplishments that we're proud of
Our program accomplished our goal of computing miller values from a given data set of measured values! Remarkably, our program even found errors in previously computed miller unit values calculated by the historically used method of manually imputing into an excel template. This new method cuts down 67.5% of the work needed to calculate miller unit values as compared to the previously used methods.
📚 What we learned
From this project, we significantly enhanced our file i/o abilities (especially when it came to new file types such as csv), as well as our general understanding of lists and other staple coding features.
🚧 What's next
Additional features would include: (i) a graphical output with miller unit values given for each sample, (ii) Including an interface that could actively display statistics when calculating the error in β-Galactosidase measurements, (iii) implementing calculations for further miller unit calculations such as induction or repression ratios.
👥 Team
- Carter Gray: Conceived the project idea, development
- Ryan Huffman: Development
🏁 Submission Category / Track
- Beginner Track and General Track
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