Homework

Weekly homework submissions:

  • Week 1 Homework: Microbiome-Tuned Skincare week

    1. First, describe a biological engineering application or tool you want to develop and why After the first week of the How To Grow Almost Anything course and the projects that were presented by the panel, I decided to focus on an area that has always fascinated me: skincare and cosmetics. I have personally struggled to find products that actually worked for my skin. Some creams caused dryness, others triggered breakouts, and many were ineffective despite high prices and flashy marketing. Over time, I realized that this frustration is common—most skincare follows a “one-size-fits-all” approach, categorizing skin as oily, dry, combination, or sensitive. While these categories are a helpful starting point, they fail to capture the biological complexity and uniqueness of each person’s skin.

  • Week 2 Homework: DNA Read, Write & Edit

    PART 1: Gel Art For the Gel Art part, I searched Roman’s Gallery and chose the little smiley face :). PART 3: DNA Design Challenge 3.1 Choose Your Protein The protein I have chosen for this DNA design challenge is Sonic Hedgehog (Shh), a critical signaling molecule involved in embryonic development, tissue patterning, and organ formation. Shh plays a central role in directing cell fate decisions during development, and mutations in this protein are linked to severe developmental disorders. Its importance in biology, combined with the fact that it is well-characterized and has a known amino acid sequence, makes it an ideal candidate for this exercise.

  • Week 3 Homework: Lab Automation

    Python Script for Opentrons Artwork I used the opentrons-art.rcdonovan.com site to make a shrimp design: The script made with collab: from opentrons import types

  • Week 4 Homework: Protein Design I

    Homework: Protein Design I 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) In a 500-gram piece of meat, you are consuming approximately: 7.5275 × 10^23 amino acids

  • Week 5 Homework: Protein Design Part II

    Week 5 - Protein Design Part II Part A: SOD1 Binder Peptide Design (From Pranam) Part 1: Generate Binders with PepMLM SOD1 sequence with A4V mutation: ATKVVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ Peptide # Peptide Sequence Perplexity Score 1 WHYYVTAIEWKK 25.725023 2 KHYYWVAIRWKK 27.40476 3 HRSPVVGVALKK 12.718177 4 WRYPVAAIELKE 17.102567 5 FLYRWLPSRRGG N/A Part 2: Evaluate Binders with AlphaFold3 Peptide # Peptide Sequence ipTM 1 WHYYVTAIEWKK 0.31 2 KHYYWVAIRWKK 0.4 3 HRSPVVGVALKK 0.41 4 WRYPVAAIELKE 0.3 5 FLYRWLPSRRGG 0.28 Peptide # Peptide Sequence ipTM Binding Description 1 WHYYVTAIEWKK 0.31 Binds near the surface of the β-barrel;; mostly surface-exposed. 2 KHYYWVAIRWKK 0.40 Appears bound on the β-barrel and dimer interface, surface-bound 3 HRSPVVGVALKK 0.41 Localized near the β-barrel surface, surface-bound. 4 WRYPVAAIELKE 0.30 Surface-bound,minimal contact with N-terminal residues, approaches dimer interface. 5 FLYRWLPSRRGG 0.28 Surface-bound, does not penetrate deeply into β-barrel. The ipTM scores for the PepMLM-generated peptides range from 0.30 to 0.41, slightly higher than the known binder (0.28). Peptides 2 and 3 show the highest ipTM scores, indicating stronger predicted structural confidence in the SOD1–peptide complex.

  • Week 6 Homework: Genetic Circuits Part I

    Week 6 — Genetic Circuits Part I: Assembly Technologies Assignment: DNA Assembly 1. What are some components in the Phusion High-Fidelity PCR Master Mix and what is their purpose? Some components that are found in the Phusion High-Fidelity PCR Master Mix are:

  • Week 7 Homework: Genetic Circuits Part II: Neuromorphic Circuits

    Assignment Part 1: Intracellular Artificial Neural Networks (IANNs) 1. What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? -Traditional genetic circuits typically operate on Boolean logic, which processes inputs as binary states (0 or 1). IANNs offer several advantages: -Analog Integration - unlike Boolean circuits, IANNs can process graded signals, this allows cells to respond proportionally to varying concentrations of chemicals or light. -Scalability - to achieve complex decision-making with Boolean logic, you need a massive number of gates, which places a heavy metabolic burden on the cell, IANNs can achieve classification or pattern recognition using fewer components by adjusting binding affinities or promoter strengths. -Non-Linear Processing - IANNs utilize activation functions, this allows them to filter noise and handle non-linear relationships between inputs.

  • Week 9 HW: Cell-Free Systems

    Homework Part A: General and Lecturer-Specific Questions General homework questions 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.

  • Week 10 HW: Measurement Technology

    Waters Part I — Molecular Weight To calculate the theoretical molecular weight (MW) of the eGFP sequence provided, we must account for the primary amino acid sequence and the critical internal post-translational modification that creates the fluorophore.

  1. The provided sequence contains 246 amino acids: