Homework
Weekly homework submissions:
Week 1 HW: Principles and Practices
- Biological engineering application / tool One biological engineering tool I would like to develop is a programmable biological computing platform based on synthetic genetic circuits that can sense biological inputs, perform simple computational operations, and produce interpretable outputs such as a visible color change or measurable signal. This idea comes from my interest in using synthetic biology as a medium for computation that could complement or eventually reduce reliance on energy-intensive electronic systems.
Week 2 HW: DNA Read, Write, & Edit
Part 0: Basics of Gel Electrophoresis Completed Part 1: Benchling & In-silico Gel Art After opening my Benchling account and joining the HTGAA group in Benchling, I imported the Lambda DNA. A restriction enzyme digestion was simulated in Benchling with the following enzymes:
Python Script for Opentrons Artwork For this lab, I generated an artistic design using the GUI at opentrons-art.rcdonovan.com. I decided to design some undersea animals because I really like being underwater and observing their nature. Given that in my node’s lab there are only fluorescent green and red, I decided to draw a red crab, a green turtle, and a red and green fish.
Week 4 HW: Protein Design Part 1
Part A. Conceptual Questions 1. How many molecules of amino acids do you take with a piece of 500 grams of meat? (on average an amino acid is ~100 Daltons) Amino acids have an average mass of about 100 Daltons, which is approximately 100 g per mole. If we assume that most of the mass of meat comes from proteins, we can estimate the number of amino acids in 500 g of meat to be 3*10^24 amino acid molecules.
Week 7 HW: Genetic Circuits Part 2
Part 1: Intracellular Artificial Neural Networks (IANNs) What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? There is currently a need for non-binary biological computing, where an input for example is analog, or we want an output to be graded, this is where Intracellular Artificial Neural Networks are useful. This means that outputs can be low, medium, high. We can manupulate the inputs/outputs as if they were signals (using low-pass, high-pass, band-pass, etc filters) and with mathematical functions, rather than strictly Boolean ON/OFF outputs. IANNs combine many inputs simultaneously, and each input has a different “weight”. They can also detect patterns that are nonlinear and create thresholds. IANNs also help with scalability, as we can include many layers (multi-layers) while dealing with boolean circuits, and gates can get very messy.
General homework questions Explain the main advantages of cell-free protein synthesis over traditional in vivo methods, specifically in terms of flexibility and control over experimental variables. Name at least two cases where cell-free expression is more beneficial than cell production. The main advantage of cell-free protein synthesis is the complete control we can get over experimental conditions. Unlike in vivo systems, where the cell regulates gene expression, metabolism, and resource allocation, in cell-free systems, the researcher directly defines all components and conditions.
Week 11 HW: Bioproduction & Cloud Labs
Part A: The 1,536 Pixel Artwork Canvas | Collective Artwork Unfortunately, I was not able to contribute to the canvas that week as I had no signal. The idea of people from all over the world collaborating on a single piece, everyone bringing their own little piece of creativity into something unified through synthetic biology, is such a cool concept.