Homework

Weekly homework submissions:

  1. First, describe a biological engineering application or tool you want to develop and why. This could be inspired by an idea for your HTGAA class project and/or something for which you are already doing in your research, or something you are just curious about.

  • Week 02 HW: DNA Read, write, and edit

    This week, we evaluated the different methods to read, write, and edit DNA. Part 1: Benchling & In-silico Gel Art Make a free account at benchling.com Import the Lambda DNA. Simulate Restriction Enzyme Digestion with the following Enzymes: EcoRI HindIII BamHI KpnI EcoRV SacI Sall Create a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks. I decided to elaborate on the design of a square wine glass. This design is new, and it provides a fresh look for wine.

  • Week 03 HW: Lab automation

    Assignment: Python Script for Opentrons Artwork — DUE BY YOUR LAB TIME!

  1. Your task this week is to Create a Python file to run on an Opentrons liquid handling robot.
  2. Review this week’s recitation and this week’s lab for details on the Opentrons and programming it.
  3. Generate an artistic design using the GUI at opentrons-art.rcdonovan.com. Using the coordinates from the GUI, follow the instructions in the HTGAA26 Opentrons Colab to write your own Python script which draws your design using the Opentrons. You may use AI assistance for this coding — Google Gemini is integrated into Colab (see the stylized star bottom center); it will do a good job writing functional Python, while you probably need to take charge of the art concept. If you’re a proficient programmer and you’d rather code something mathematical or algorithmic instead of using your GUI coordinates, you may do that instead. 4. If you use AI to help complete this homework or lab, document how you used AI and which models made contributions.
  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) 500 grams of protein, approximately, has 20% of protein.
  2. Why do humans eat beef but do not become a cow, eat fish but do not become fish? This phenomenon occurs because humans are living beings with a special anatomy; indeed, we have a relatively smaller colon and larger small intestine, which shows that our system is prepared to process high-protein diets. These characteristics, along with others like gastric acidity, allow humans to ingest beef and fish, and thought-out gastric system becomes a big part of food, especially meat, in amino acids that our body can use to synthesize proteins that we need. This is why it is important to have a balanced diet with an adequate amount of protein.
  1. Begin by retrieving the human SOD1 sequence from UniProt (P00441) and introducing the A4V mutation.
  2. Using the PepMLM Colab linked from the HuggingFace PepMLM-650M model card:
  3. Generate four peptides of length 12 amino acids conditioned on the mutant SOD1 sequence.
  4. To your generated list, add the known SOD1-binding peptide FLYRWLPSRRGG for comparison.
  1. What are some components in the Phusion High-Fidelity PCR Master Mix and what is their purpose? The Phusion High-Fidelity PCR Master Mix is a mix that has several components that allow the user to add only the DNA template, primers, and water to perform PCR. Advantages: Robust Reactions - Maximal success with minimal optimization. Extreme Fidelity - > 50X greater than Taq High Speed - Dramatically reduced extension times (10X faster than Pfu) High Yield - Increased product yield using minimal amount of enzyme. Versatile - Can be used for routine per as well as long or difficult templates. 2. What are some factors that determine primer annealing temperature during PCR?
  1. What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? Boolean network models contain a set of variables; each variable might have one of two possible values: false or true. In contrast, IANNs can approximate a wide range of nonlinear functions, obtaining multi-level outputs, which allows taking more precise decisions. IANNs are designed to work with continuous signals, so they can be more robust to that variability than a circuit, making it easy to build big and complex systems. They can incorporate time and dynamics.
  1. 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. Cell-free protein synthesis is usually better than traditional in vivo expression systems because it is an open system. It allows direct tuning of the reaction conditions, monitoring the process, and adding components like labels, chaperones, cofactors, or non-natural amino acids much more easily than in living cells.
  1. Please identify at least on6e (ideally many) aspect(s) of your project that you will measure. It could be the mass or sequence of a protein, the presence, absence, or quantity of a biomarker, etc. The main measurable aspect of this project is the presence or absence of the A118G polymorphism in the OPRM1 gene.
  2. Please describe all of the elements you would like to measure, and furthermore describe how you will perform these measurements.
  1. Contribute at least one pixel to this global artwork experiment before the editing ends on Sunday 4/19 at 11:59 PM EST. A personalized URL was sent to the email address associated with your Discourse account, and you can discuss the artwork on the Discourse. If you did not have a chance to contribute, it’s okay, just make sure you become a TA this fall! 😉 Although I was not able to contribute a pixel, I noticed the suggestion about becoming a TA this fall. I think it could be an interesting opportunity, as it would allow for more involvement in collaborative projects like this one and a way to support the course community.